Main Citations

Some citations to my papers:

Kanellopoulos D (2013) Intelligent Multimedia Technologies for Networking Applications: Techniques and Tools. IGI Global

• Auh, Y., & Sim, H. R. (2019). Uses of social network topology and network–integrated multimedia for designing a large–scale open learning system: case studies of unsupervised featured learning platform Design in South Korea. Multimedia Tools and Applications, 78(5), 5445–5462. IF (2018): 1.541
• Meddeb, M. (2016). Region–of–interest–based video coding for video conference applications (Doctoral dissertation, Telecom ParisTech).
• Jitsi (from Wikipedia). Available at: https://en.wikipedia.org/wiki/Jitsi

Kanellopoulos D. and Sharma V.K. (2020) Survey on power–aware optimization solutions for MANETs. Electronics (MDPI). Vol. 9, No. 7, 1129. DOI: 10.3390/electronics9071129 IF(2019): 2.412

• Amirtharaj, S., & Sabapathi, T. (2021). Cross Layer Approach and ANFIS based Optimized Routing in Wireless Multi-Hop Ad Hoc Networks. Wireless Personal Communications (Springer), 1-23. IF(2019): 1.061
• Yockey, J., Campbell, B., Coyle, A., & Hunjet, R. (2020, November). Emulating Low Probability of Detection Algorithms. In 2020 30th International Telecommunication Networks and Applications Conference (ITNAC) (pp. 1-6). IEEE.

Kanellopoulos D., and Gite P. (2020). A probability-based clustering algorithm with CH election for expanding WSN life span. Int. J. of Electronics, Communications, and Measurement Engineering. Vol. 9, No. 1, pp. 1–14.

• Huo, J., Yang, J., & Al-Neshmi, H. M. M. (2020). Design of Layered and Heterogeneous Network Routing Algorithm for Field Observation Instruments. IEEE Access, 8, 135866-135882. (IF:3.745)

Fleury M., Kanellopoulos D., and Qadri N.Ν. (2019). Video streaming over MANETs: An overview of techniques. Multimedia Tools and Applications (Springer). Vol. 78, Issue 16, pp. 23749–23782. Impact Factor (2018): 1.541

• Rodrigues, C. K. D. S., & Rocha, V. (2021). Enhancing BitTorrent for efficient interactive video-on-demand streaming over MANETs. Journal of Network and Computer Applications (Elsevier), Volume 174, 15 January 2021, 102906.
• Boulaiche, M. (2020). Survey of Secure Routing Protocols for Wireless Ad Hoc Networks. Wireless Personal Communications (Springer), 114(1), 483-517.
• Ebrahim, M.E., & Mohmmed, A. (2019). A survey on multimedia over 5G Networks for D2D communication based Wi–Fi Direct technology. The 54th Annual Conference on Statistics, Computer Sciences and Operation Research 9–11 Dec. 2019.
• Rodrigues, C., & Rocha, V. (2020, June). BIB–R: Uma Nova Adaptação do BitTorrent para Streaming de Vídeo sob Demanda ante Clientes Interativos em MANETs. In Anais do XIX Workshop em Desempenho de Sistemas Computacionais e de Comunicação (pp. 1–12). SBC.

Kanellopoulos D. (2019). Recent progress on QoS scheduling for Mobile Ad hoc Networks. Journal of Organizational and End User Computing. Vol. 31, No. 3, pp. 37–66, ISI Impact factor (2018): 0.759

• Mohammed Aljubayri, Zhaohui Yang, Mohammed Shikh-Bahaei (2021) Cross-layer Multipath Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks. IET Communications (Wiley).
• Almazok, S. A., & Bilgehan, B. (2020). A novel dynamic source routing (DSR) protocol based on minimum execution time scheduling and moth flame optimization (MET-MFO). EURASIP Journal on Wireless Communications and Networking, 2020(1), 1-26.
• Jubair, M. A., Mostafa, S. A., Muniyandi, R. C., Mahdin, H., Mustapha, A., Hassan, M. H., ... & Mahmood, A. J. (2019). Bat Optimized Link State Routing Protocol for Energy–Aware Mobile Ad–Hoc Networks. Symmetry, 11(11), 1409. ISI Impact factor (2018): 2.143
• Rasheed, M., & Sarhan, M. A. (2019). Characteristics of Solar Cell Outdoor Measurements Using Fuzzy Logic Method. Insight–Mathematics, 1(1).
• Mostafavi, S., Hakami, V., & Paydar, F. (2020). A QoS–Assured and Mobility–Aware Routing Protocol for MANETs. JOIV: International Journal on Informatics Visualization, 4(1), 1–9.
• Mustafa, M. A., Rasheed, M. H., & Salih, O. M. (2020). Low energy consumption in MANET network. Periodicals of Engineering and Natural Sciences, 8(2), 904-915.
• Mustafa, A. S., Al–Heeti, M. M., Hamdi, M. M., & Shantaf, A. M. (2020, June). Performance Analyzing the Effect of Network Size on Routing Protocols in MANETs. In 2020 International Congress on Human–Computer Interaction, Optimization and Robotic Applications (HORA) (pp. 1–5). IEEE.

Kanellopoulos D. (2019). Congestion control for MANETs: An overview. ICT Express (Elsevier), Vol. 5, Issue 2, pp.77–83.

• Krishnan, C. G., Robinson, Y. H., Julie, E. G., Bamini, A. A., Kumar, R., & Thong, P. H. (2021). Hybrid Cache Management in Ad Hoc Networks. Wireless Personal Communications (Springer), 1-23.
• Hanin, M. H., Amnai, M., & Fakhri, Y. (2021). New adaptation method based on cross layer and TCP over protocols to improve QoS in mobile ad hoc network. International Journal of Electrical & Computer Engineering (2088-8708), 11(3).
•  Rodrigues, C. K. D. S., & Rocha, V. (2021). Enhancing BitTorrent for efficient interactive video-on-demand streaming over MANETs. Journal of Network and Computer Applications (Elsevier), 174, 102906.
• Muchtar, F., Abdullah, A. H., Al–Adhaileh, M., & Zamli, K. Z. (2020). Energy conservation strategies in Named Data Networking based MANET using congestion control: A review. Journal of Network and Computer Applications (Elsevier), Vol. 152, 102511. IF (2018): 5.273
• Wen, S., Deng, L., Shi, S., Fan, X., & Li, H. (2020). Distributed Congestion Control via Outage Probability Model for Delay-Constrained Flying Ad Hoc Networks. Wireless Communications and Mobile Computing, 2020. Article ID 8811840 | https://doi.org/10.1155/2020/8811840 [IF: 1.819]
• Rajashanthi, M., & Valarmathi, K. (2020). Energy-efficient multipath routing in networking aid of clustering with OGFSO algorithm. Soft Computing (Springer), 24(17), 12845-12854. IF (2018): 2.784
• Krishnamoorthy, D., Vaiyapuri, P., Ayyanar, A., Harold Robinson, Y., Kumar, R., Long, H. V., & Son, L. H. (2020). An Effective Congestion Control Scheme for MANET with Relative Traffic Link Matrix Routing. Arabian Journal for Science and Engineering (Springer), 1–11. IF (2018): 1.518
• Praghash, K., & Ravi, R. (2019). An Enhanced Steiner Hierarchy (E–SH) Protocol to Mitigate the Bottleneck in Wireless Sensor Networks (WSN). Wireless Personal Communications (Springer), 105(4), 1285–1308. IF (2018): 0.959
• Garaaghaji, A., & Alfi, A. (2020). Robust performance rate control to enhance MANET networks routing issue. Journal of Electrical Engineering & Technology (Springer), 15(1), 477–486. IF (2017): 0.597
• Iqtidar Ali, Tariq Hussain, Kamran khan, Arshad Iqbal, & Fatima Perviz (2021).The impact of IEEE 802.11 contention window on the performance of Transmission Control Protocol in mobile ad-hoc networks.  Advances in Distributed Computing and Artificial Intelligence Journal.
• Liu, X. (2020). Ad Hoc Network Congestion Management Based on Entropy and Third-Party Nodes (Doctoral dissertation, ResearchSpace@ Auckland).
• Mirzaeinnia, A., Mirzaeinia, M., & Rezgui, A. (2020). Latency and Throughput Optimization in Modern Networks: A Comprehensive Survey. arXiv preprint arXiv:2009.03715.
• Pillai, B., Tomar, D. S., & Khare, A. K. (2020). A Model for Early Detection and Avoidance of Congestion in MANET (No. 3161). EasyChair.
• Olusanya, M. O., & Vincent, O. R. (2020, March). A MANET–based Emergency Communication System for Environmental Hazards Using Opportunistic Routing. In 2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS) (pp. 1–6). IEEE.
• Sandeep, J. (2019). Ant Colony Based Mechanism for Increasing Life Time of critical nodes. Journal of Engineering Science and Technology Review, 12(5), 25–30. (Scopus indexed)
• Himanshu Sharma, Omkar Singh, Vinay Rishiwal, MIH Ansari (2019, August) Energy Efficient Routing Protocol Prolonging Network Lifetime for MANETs. Int. Journal of Scientific & Technology Research, 8(8), 1902–1908.
• Reddy, Y. N., & Srinivas, P. V. S. (2018). A Routing Delay Predication Based on Packet Loss and Explicit Delay Acknowledgement for Congestion Control in MANET. International Journal of Communication Networks and Information Security, 10(3), 447. (Scopus indexed)
• Nabou, A., Laanaoui, M. D., Ouzzif, M., & El Houssaini, M. A. (2020, March). Normality Test to Detect the Congestion in MANET by Using OLSR Protocol. In Proceedings of the 3rd International Conference on Networking, Information Systems & Security (pp. 1–5).
• Pawar, M. V., & Anuradha, J. (2020) Intrusion Detection and Prevention in WSN and MANET using Machine Learning Techniques and Existing Challenges. International Journal of Advanced Science and Technology, Vol. 29, No. 3, pp. 306–328
• Amraoui, H., Habbani, A., & Hajami, A. (2018, October). Reducing Network Topology over Smart Digital Mobile Environment Using Linear Programming Approach. In Proceedings of the 2nd International Conference on Smart Digital Environment (pp. 1–8). ACM.
• Mirzaeinnia, A., Mirzaeinia, M., & Rezgui, A. (2020). Latency and Throughput Optimization in Modern Networks: A Comprehensive Survey. arXiv preprint arXiv:2009.03715.

Kanellopoulos, D. (2017). QoS routing for multimedia communication over wireless mobile ad hoc networks: A survey. International Journal of Multimedia Data Engineering and Management, Vol. 8, No. 1, pp.42-71 [Emerging Sources Citation Index]

• Alghamdi, S. A. (2020). Three-Tier Architecture Supporting QoS Multimedia Routing in Cloud-Assisted MANET with 5G Communication (TCM5G). Mobile Networks and Applications (Springer), 25(6), 2206-2225. IF (2019): 2.602
• Li, M., & Li, H. (2020). Application of deep neural network and deep reinforcement learning in wireless communication. PLoSONE 15(7):e0235447.https://doi.org/10.1371/journal.pone.0235447
• Murugan, S., & Veeramanikandan, V. (2020, February). Performance of Packet Loss Differentiation Model by using Cuckoo Search Back–Propagation Neural Network (CSBPNN) for Mobile Ad–hoc Networks. In 2020 International Conference on Inventive Computation Technologies (ICICT) (pp. 307–311). IEEE.
• Tien, N.X., Rhee, J.M., & Park, S.Y. (2018). A Novel Effective Multipath Routing Technique Providing High Availability in Wireless Networks. Electronics (MDPI), 7(4), 42. IF (2017): 2.110
• Guck, J.W., Van Bemten, A., Reisslein, M., & Kellerer, W. (2017). Unicast QoS routing algorithms for SDN: A comprehensive survey and performance evaluation. IEEE Communications Surveys & Tutorials, 20(1), 388–415. IF: 17.18

Sakkopoulos E., Paschou M., Panagis Y., Kanellopoulos D., Eftaxias G., and Tsakalidis A. (2015). e-souvenir Appification: QoS Web based Media delivery for Museum Apps. Electronic Commerce Research (Springer), 15(1), 5-24. ISI Impact Factor (2015): 1.275

• Liu, C. L., Su, K. W., & Uang, S. T. (2019). The effects of layout types and spatial information display types on presence and spatial identification for the elderly in the 3D virtual art gallery. Journal of Ambient Intelligence and Humanized Computing, 10(9), 3439–3451. IF(2017): 1.423
• Poongodi, P., & Kumareshan, N. (2016). Analysis of dynamic overlay architecture for the Quality of Experience (QoE) improvement in wireless networks. Wireless Personal Communications, 90(2), 503–514. IF:(2015): 0.701
• Lakshmi, N. S. R., Bhalaji, N., & Sivakumar, B. (2016). On the construction of QoS based overlay architecture for wireless local area network. Wireless Personal Communications, 90(2), 817–829. IF(2015): 0.701
• Palaiokrassas, G., Voulodimos, A., Konstanteli, K., Vretos, N., Osborne, D. S., Chatzi, E., ... & Varvarigou, T. (2016). Social media interaction and analytics for enhanced educational experiences. IEEE MultiMedia, 23(1), 26–35. IF(2015): 1.361
• Francese, R., & Risi, M. (2016). Supporting elderly people by ad hoc generated mobile applications based on vocal interaction. Future Internet, 8(3), 42. [Emerging Sources Citation Index (Thomson Reuters)]
• Baker, E.J., Bakar, J.A.A., & Zulkifli, A.N. (2017, October). Elements of museum mobile augmented reality for engaging hearing impaired visitors. In AIP Conference Proceedings (Vol. 1891, No. 1, p. 020033). AIP Publishing.
• Baker, E.J., Bakar, J.A.A., & Zulkifli, A.N. (2017). Mobile augmented reality elements for museum hearing impaired visitors’ engagement. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2–12), 171–178.
• Kountouris, A., & Sakkopoulos, E. (2018, November). Survey on intelligent personalized mobile tour guides and a use case walking tour App. In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 663–666). IEEE.

Sanandaji A., Jabbehdari S., Balador A., and Kanellopoulos D. (2013). MAC layer misbehavior in MANETs. IETE Technical Review (Taylor & Francis), 30(4): 324-335. ISI Impact Factor: 1.304

• Zhang, Y., & Lazos, L. (2018). Misbehavior in Multi-Channel MAC Protocols. IEEE Transactions on Dependable and Secure Computing, 17(4), 760-774.
• Tissera, M., Doss, R., Li, G., Mak–Hau, V., & Batten, L. (2018). A novel approach for information discovery in wireless sensor grids. Journal of Network and Systems Management (Springer), 26(3), 640–662. IF: 1.588
• Illa Ul Rasool et al. (2017). A review of wireless access vehicular environment multichannel operational medium access control protocols: Quality–of–service analysis and other related issues.
• Rasool, I.U., Zikria, Y.B., & Kim, S.W. (2017). A review of wireless access vehicular environment multichannel operational medium access control protocols: Quality–of–service analysis and other related issues. International Journal of Distributed Sensor Networks (SAGE), 13(5), 1550147717710174. IF: 0.906
• Jhaveri, R.H., & Patel, N.M. (2015). A sequence number based bait detection scheme to thwart grayhole attack in mobile ad hoc networks. Wireless Networks (Springer), 21(8), 2781–2798.
• Razaque, A., & Elleithy, K. (2016). Nomenclature of Medium Access Control protocol over wireless sensor networks. IETE Technical Review, 33(2), 160–171. IF(2015): 1.304
• Musaddiq, A., Hashim, F., Ujang, C.A.B.C., & Ali, B. M. (2015). Survey of channel assignment algorithms for multi–radio multi–channel wireless mesh networks. IETE Technical Review, 32(3), 164–182.
• Ismail, R., Zulkifli, C. Z., & Samsudin, K. (2016). Routing protocols for mobile ad-hoc network: A qualitative comparative analysis. JURNAL TEKNOLOGI, 78(8), 1–10. Emerging Sources Citation Index
• Tissera, M., Doss, R., Li, G., & Batten, L. M. (2015, June). Novel approach for information discovery in autonomous wireless sensor networks. In International Conference on Future Network Systems and Security (pp. 47–60). Springer International Publishing.
• Sahoo, A. J., Akhtar, M., & Khusru, A. (2014). Determining the possibilities and certainties in network participation for MANETS. arXiv preprint arXiv:1401.0875.

Kanellopoulos D. (2014) "Multimedia networking issues for digital video libraries". The Electronic Library (Emerald), Vol. 32, No.6. pp. 898-922. ISI Impact Factor (2015): 0.436

• Kovačević, I., Bach, M. P., & Jaković, B. (2018). Always-On Sport Content Multimedia Delivery Over Internet in Croatia. In Always-On Enterprise Information Systems for Modern Organizations (pp. 88-111). IGI Global.

Kanellopoulos D. et al. (2012) Implementing a zoomable web browser with annotation features for managing libraries of high quality images. International Journal of Innovative Computing, Information and Control. 8(10B), 7725-7235, October 2012.

• Kim, K. H., & Cho, H. G. (2015). Preference-customizable clustering system for smartphone photographs. Journal of Ambient Intelligence and Smart Environments, 7(2), 201-220. ISI Impact Factor: 0.707   
• Maiseli, B., Wu, C., Mei, J., Liu, Q., & Gao, H. (2014). A robust super-resolution method with improved high-frequency components estimation and aliasing correction capabilities. Journal of the Franklin Institute, 351(1), 513-527. ISI Impact Factor: 2.327

Mikóczy E., Vidal I., Kanellopoulos D. (2012) IPTV evolution towards NGN and hybrid scenarios. Informatica  36(1): 3-12. [Emerging Sources Citation Index]

• Seiwert, N. (2014). Flow Optimization for concurrent Multimedia Traffic in Software Defined Networks (Doctoral dissertation, Saarland University).

Balador A., Movaghar A., Jabbehdari S., Kanellopoulos D. (2012) A novel contention window control scheme for IEEE 802.11 WLANs. IETE Technical Review (Taylor & Francis), 29(3): 202-212. ISI Impact Factor: 1.304

• Zerguine, N., Mostefai, M., Aliouat, Z., Slimani, Y. (2020). Intelligent CW selection mechanism based on Q-learning (MISQ). Ingénierie des Systèmes d’Information, Vol. 25, No. 6, pp. 803-811. https://doi.org/10.18280/isi.250610
• Bhavadharini, R. M., Karthik, S., Karthikeyan, N., & Paul, A. (2018). Wireless networking performance in IoT using adaptive contention window. Wireless Communications and Mobile Computing (Hindawi/Wiley), 2018.
• Wu, G., & Xu, P. (2018). Improving Performance by a Dynamic Adaptive Success–Collision Backoff Algorithm for Contention–Based Vehicular Network. IEEE Access, 6, 2496–2505. IF: 3.557
• Ali, R., Kim, S. W., Kim, B. S., & Park, Y. (2018). Design of MAC Layer Resource Allocation Schemes for IEEE 802.11 ax: Future Directions. IETE Technical Review, 35(1), 28–52. IF: 1.304
• Tiwari, N., & Rishi, O.P. (2017). Improved VoIP QoS over Wireless Networks. International Journal of Advanced Research in Computer Science, 8(5).
• Alkadeki, H., Wang, X., & Odetayo, M. (2016). Improving performance of IEEE 802.11 by a dynamic control backoff algorithm under unsaturated traffic loads. arXiv preprint arXiv:1601.00122.
• Tanjeem, F., Uddin, M. Y. S., & Rahman, A. A. (2015, January). Wireless media access depending on packet size distribution over error–prone channels. In Networking Systems and Security (NSysS), 2015 International Conference on (pp. 1–7). IEEE.
• Ranganathan, R., & Kannan, K. (2015). Enhancing the Selection of Backoff Interval Using Fuzzy Logic over Wireless Ad Hoc Networks. The Scientific World Journal (Hindawi), 2015.
• Maadani, M., & Motamedi, S. A. (2015). Contention Window Adjustment in IEEE 802.11–Based Industrial Wireless Networks. World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 9(11), 1267–1272.
• Hassan, W. H. B. W. (2015). Effects of enhancing performance in fiber–wireless networks (Doctoral dissertation, Victoria University).
• Devipriya, M., Nithya, B., & Mala, C. (2015). Hashing based distributed backoff (HBDB) mechanism for IEEE 802.11 wireless networks. J. Internet Services Inf. Security, 5(3), 1–18.
• Sotheara, S., Aomi, N., Ando, T., Jiang, L., Shiratori, N., & Shimamoto, S. (2014, December). Effective data gathering protocol in WSN–UAV employing priority–based contention window adjustment scheme. In Globecom Workshops (GC Wkshps), 2014 (pp. 1475–1480). IEEE.
• Borges, L. M., Velez, F. J., & Oliveira, R. (2014, April). A two–phase contention window control scheme for decentralized wireless networks. In Wireless Communications and Networking Conference (WCNC), 2014 IEEE (pp. 1550–1555). IEEE.
• Saraireh, M., AL–Saraireh, J., & Saraireh, S. (2014). A Novel Adaptive Contention Window Scheme for IEEE 802.11 MAC Protocol. Trends in Applied Sciences Research, 9(6), 275–289.
• Ja’afer, A. S., Saraireh, S., Saraireh, M., & Younis, M. B. (2014). Adaptive Distributed Inter Frame Space for IEEE 802.11 MAC Protocol. Communications and Network, 2014.
• Habbal, A. (2014). TCP Sintok: Transmission control protocol with delay–based loss detection and contention avoidance mechanisms for mobile ad hoc networks (Doctoral dissertation, Universiti Utara Malaysia).

Kanellopoulos D. and Panagopoulos A. (2008). Exploiting tourism destinations’ knowledge in a RDF–based P2P network. Journal of Network and Computer Applications (Elsevier), 31(2), 179–200. ISI 5–Year Impact Factor: 2.485

• Estêvão, J., Carneiro, M. J., & Teixeira, L. (2020). Destination management systems’ adoption and management model: proposal of a framework. Journal of Organizational Computing and Electronic Commerce (Taylor & Francis), 1–22, [Science Citation Index Expanded]
• Chen, Y. H., Lu, E. J. L., Chang, Y. T., & Huang, S. Y. (2016). RDF–Chord: A hybrid PDMS for P2P systems. Computer Standards & Interfaces (Elsevier), 43, 53–67. IF(2015): 1.268
• Liu, M., Koskela, T., Ou, Z., Zhou, J., Riekki, J., & Ylianttila, M. (2011). Super–peer–based coordinated service provision. Journal of Network and Computer Applications (Elsevier), 34(4), 1210–1224.
• Tria, S. B., Seridi–Bouchelaghem, H., & Mokhati, F. (2016). An ontology–based context model to manage users preferences and conflicts. Informatica, 40(1), 71. [ESCI]
• Shi, M., Zhu, W., Yang, H., & Li, C. (2016). Applying semantic web and big data techniques to construct a balance model referring to stakeholders of tourism intangible cultural heritage. International Journal of Computer Applications in Technology (Inderscience), 54(3), 192–200.
• Pereira, R. L., Sousa, P. C., Barata, R., Oliveira, A., & Monsieur, G. (2015). CitySDK Tourism API–building value around open data. Journal of Internet Services and Applications (Springer), 6(1), 24. [ESCI]
• de–Laguno–Alarcón, C., Sierra–Herrezuelo, P., & Rojas–de–Gracia, M. M. (2019). Results–Oriented Influencer Marketing Manual for the Tourism Industry. In Business Transformations in the Era of Digitalization (pp. 249–275). IGI Global.
• Ruiz–Martınez, J. M., Minarro–Giménez, J. A., Castellanos–Nieves, D., Garcıa–Sánchez, F., & Valencia–Garcia, R. (2011). Ontology population: an application for the e–tourism domain. International Journal of Innovative Computing, Information and Control (IJICIC), 7(11), 6115–6134.
• Tseng, H. C., Tu, P. P. N., Lee, Y. C., & Wang, T. S. (2012). A study of user acceptance of destination management systems in Taiwan tourism with the modified technology acceptance model. Journal of Convergence Information Technology, 7(10).
• Siricharoen, W. V. (2010). Enhancing semantic web and ontologies for e–tourism. International Journal of Intelligent Information and Database Systems, 4(4), 355–372.
• Ángel García–Crespo et al. (2010) Intelligent Decision–Support Systems for e–Tourism: Using SPETA II as a Knowledge Management Platform for DMOs and e–Tourism Service Providers. International Journal of Decision Support System Technology (IJDSST) Vol. 2, No.1, pp.36–48.
• García–Crespo, Á., Colomo–Palacios, R., Gómez–Berbís, J. M., Chamizo, J., & Rivera, I. (2012). Intelligent Decision–Support Systems for e–Tourism: Using SPETA II as. Integrated and Strategic Advancements in Decision Making Support Systems, 37.
• García–Barriocanal, E., & Sicilia, M. A. (2008). On linking cultural spaces and e–tourism: An ontology–based approach. The Open Knowlege Society. A Computer Science and Information Systems Manifesto, 694–701.
• Nina Mistilis, Dimitrios Buhalis (2012) Challenges and potential of the Semantic Web for tourism. e–Review of Tourism Research (eRTR), Vol. 10, No. 2, 2012, https://ertr.tamu.edu. Special Issue – ENTER 2012 Idea Exchange.
• Bauer, L., Boksberger, P., Herget, J., Hierl, S., & Orsolini, N. (2008). The virtual dimension in tourism: Criteria catalogue for the assessment of eTourism applications. Information and Communication Technologies in Tourism 2008, 521–532.
• Wenyun, L., & Lingyun, B. (2009, December). Application and exploration of travel–service and information system based on web service. In Computational Intelligence and DeSign, 2009. ISCiD'09. Second International Symposium on (Vol. 1, pp. 438–441). IEEE.
• Colomo–Palacios, R. (2013). Semantic Technologies in Motion: From Factories Control to Customer Relationship Management. In Industrial Engineering: Concepts, Methodologies, Tools, and Applications (pp. 477–498). IGI Global.
• MAICAN, C., & Lixăndroiu, R. (2014). A PROPOSAL FOR AN INTERACTIVE SYSTEM FOR ASSISTING TOURIST DECISION MAKING. Management & Marketing, 9(2).
• Chatzitoulousis, A., Efraimidis, P. S., & Athanasiadis, I. N. (2015, September). Interoperable Multimedia Annotation and Retrieval for the Tourism Sector. In Research Conference on Metadata and Semantics Research (pp. 65–76). Springer International Publishing.
• Maria Teresa Linaza, Cristina Sarasua, Yolanda Cobos (2009) MPEG–7 Compliant Indexation Tool for Multimedia Tourist Content. Information and Communication Technologies in Tourism 2009 (pp. 249–260) Editors: Wolfram Höpken, Ulrike Gretzel and Rob Law. Publisher: Springer Vienna. Doi: 10.1007/978–3–211–93971–0_21
• Liu Wenyun, Bao Lingyun (2009) Application and Exploration of Travel–Service and Information System Based on Web Service. 2009 Second International Symposium on Computational Intelligence and Design (ISCID), Vol. 1, pp.438–441.
• Mudiyanselage, R. D. (2014). Ontology–based Search Algorithms over Large–Scale Unstructured Peer–to–Peer Networks (Doctoral dissertation, ScholarWorks@ Georgia State University).

Kanellopoulos D., Kotsiantis S. (2012) Evaluating and recommending Greek newspaper web sites using clustering. Program: Electronic Library and Information Systems (Emerald), 46(1): 71-91. ISI Impact Factor (2015): 1.00

• Nurdin, N., & Aratusa, Z. C. (2020). Benchmarking level interactivity of Indonesia government university websites. Telkomnika, 18(2), 853-859.
• Youngblood, N. E. (2018). Digital inclusiveness of health information websites. Universal Access in the Information Society (Springer), 1–12. ISI Impact Factor (2017): 1.176
• Cechinel, C., Sicilia, M. Á., SáNchez–Alonso, S., & GarcíA–Barriocanal, E. (2013). Evaluating collaborative filtering recommendations inside large learning object repositories. Information Processing & Management (Elsevier), 49(1), 34–50. ISI Impact Factor (2015): 1.397
• Mohammad Shafi, S., & Hanief Bhat, M. (2014). Performance and visibility of Indian Research Institutions on the web. VINE: The journal of information and knowledge management systems (Emerald), 44(4), 537–547. [ESCI]
• Kanagaraj, D. J., & Sudhahar, J. C. (2015). Website quality: imperatives for effective industrial marketing through websites' usage intensity augmentation. International Journal of Electronic Customer Relationship Management, 9(4), 203–219.
• Naheem, K. T., & Saraswati Rao, M. (2017). Webometric analysis of Telugu News Paper websites: An evaluative study using Alexa Internet. International Journal of Digital Library Services (IJODLS), 7(2), 26-32.
• Naheem, K. T. (2016). Malayalam News Paper Websites: A Webometric Study Using “Alexa Internet”. International Journal of Digital Library Services, 6(3), 67–75.
• Pandit, A. S., Vaishali, K., & Bhagwanrao, R. V. (2016). Marathi News Paper websites: A webometric study. International Journal of Library and Information Studies, 6(4), 52-60.
•  Odeyemi, O. (2017). Webometric analysis of Nigerian Newspapers Websites. International Journal of Digital Library Services, 7(4), 13-20.
• Arman, M., Hajipoor, H., & Sohrabi, B. (2015). Study of the Automatic Evaluation of Website Quality from Customer Insight: A Case Study of the Most Visited News Websites as Influential Social Media Tool. In Strategic Customer Relationship Management in the Age of Social Media (pp. 178–197). IGI Global.

Kanellopoulos D. (2011) Ontology-driven knowledge management for Cognitive Networks. International Journal of Enterprise Network Management (Inderscience), 4(3): 229-246.

• Zhang, D. P., & Kang, Q. (2012). The Stability of Signal to Interference and Noise Ratio with Powers and Gains Change in Cognitive Radio Network. Sensor Letters, 10(8), 1798-1805.
• Valadares, C. (2014). A Multiagent Based Context-Aware and Self-Adaptive Model for Virtual Network Provisioning (Doctoral dissertation, PUC-Rio).

Kanellopoulos D. (2011) Quality of Service in networks supporting cultural multimedia applications. Program: Electronic Library and Information Systems (Emerald), 45(1): 50-66. ISI Impact Factor (2015): 1.00

• Nagarkar, S. (2019). Use of ICT for quality enhancement and sustainablity in libraries. Shubham Publications. ISBN: 978–93–83144–60–0.
• Hsu, T. Y., Liang, H., Chiou, C. K., & Tseng, J. C. (2018). CoboChild: a blended mobile game–based learning service for children in museum contexts. Data Technologies and Applications. 5–Year Impact Factor: 1.5
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Kanellopoulos D. (2012) Semantic annotation and retrieval of documentary media objects. The Electronic Library (Emerald), 30(5): 721-747. ISI Impact Factor (2015): 0.436

• Borges, P. R. S., & Silveira, I. F. (2019). Adding and Segmenting Educational Videos: Experiences of Teacher Users in an Educational Portal. IEEE Access, 7, 87996–88011. IF: 4.098.
• Dimoulas, C., Veglis, A., & Kalliris, G. (2015). Audiovisual hypermedia in the semantic Web. In Encyclopedia of Information Science and Technology, Third Edition (pp. 7594–7604). IGI Global.

Kanellopoulos D. (2010) Intelligent multimedia engines for multimedia content adaptation. International Journal of Multimedia Intelligence and Security (Inderscience), 1(1): 53-75.

• T. Miyosawa (2011) QoE Modeling and MPEG-21 DIA Multimedia Framework in Telecommunication and Broadcasting Convergence” The 2011 International Conference on Internet Computing. ICOMP'11.

Kanellopoulos D. (2010) Current and future directions of multimedia technology in tourism. International Journal of Virtual Technology and Multimedia (Inderscience), 1(2): 187-206.

• Tennent, P. R. (2014). Augmented analyses: supporting the study of ubiquitous computing systems (Doctoral dissertation, University of Glasgow).

Kanellopoulos D. and Lazarinis F. (2010) Developing a localization indicator for chain hotel websites: A Greek case study. International Journal of Business Information Systems (Inderscience), 5(3): 309–327. 

• Daniel Leung, Heey Lee; Rob Law (2011) “Adopting Web 2.0 technologies on chain and independent hotel websites: A case study of hotels in Hong Kong”. Information and Communication Technologies in Tourism 2011, Volume-On Page: 229-240.

Lian S., Kanellopoulos D. and Ruffo. G. (2009) Recent advances in multimedia information system security. Informatica, 33(1): 3-24. [Emerging Sources Citation Index]

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• Jinwei Wang, Shiguo Lian. (2012). On the hybrid multi–watermarking. Signal Processing (Elsevier), 92(4), 893–904. IF(2015): 2.063
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• Yu, Z., Wang, C., Thomborson, C., Wang, J., Lian, S., & Vasilakos, A. V. (2012). A novel watermarking method for software protection in the cloud. Software: Practice and Experience, 42(4), 409–430. IF (2015):  0.652
• Lian, S., & Chen, X. (2012). Lightweight secure multimedia distribution based on homomorphic operations. Telecommunication Systems (Springer), 49(2), 187–197. IF (2015):  0.822
• Yang, H. Y., Bao, D. W., Wang, X. Y., & Niu, P. P. (2012). A robust content based audio watermarking using UDWT and invariant histogram. Multimedia Tools and Applications (Springer), 57(3), 453–476. IF (2015):  1.331
• Wang, X. Y., Niu, P. P., Yang, H. Y., & Chen, L. L. (2012). Affine invariant image watermarking using intensity probability density–based Harris Laplace detector. Journal of Visual Communication and Image Representation (Elsevier), 23(6), 892–907. IF (2015):  1.530
• Liu, G., Wang, J., Lian, S., & Wang, Z. (2011). A passive image authentication scheme for detecting region–duplication forgery with rotation. Journal of Network and Computer Applications (Elsevier), 34(5), 1557–1565. 5–Year IF: 2.485
• Jobin Abraham and Varghese Paul (2011). Watermarking Grayscale Images using Text for Copyright Protection, International Journal of Computer Applications (0975 – 8887) Vol. 31– No. 9, October 2011.
• Wang, X. Y., Ma, T. X., & Niu, P. P. (2011). A pseudo–Zernike moment based audio watermarking scheme robust against desynchronization attacks. Computers and Electrical Engineering (Elsevier), 37(4), 425–443. IF (2015): 1.084
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• Luo, X., Liu, F., Lian, S., Yang, C., & Gritzalis, S. (2011). On the typical statistic features for image blind steganalysis. IEEE Journal on Selected Areas in Communications, 29(7), 1404–1422. IF (2015):  3.672.
• Hong–ying Yang, Xiang–yang Wang and Tian–xiao Ma. (2011). A robust digital audio watermarking using higher–order statistics. AEU – International Journal of Electronics and Communications (Elsevier), 65(6), 560–568. IF(2015):  0.786
• Hong–ying Yang et al. (2011). A content–based digital image watermarking scheme resistant to local geometric distortions. Journal of Optics, 13(1). IF (2015):  1.847
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• Wang, X. Y., Niu, P. P., Meng, L., & Yang, H. Y. (2011). A robust content based image watermarking using local invariant histogram. Multimedia Tools and Applications (Springer), 54(2), 341–363. IF (2015):  1.331
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• Shi, L., Lin, F., Yang, T., Qi, J., Ma, W., & Xu, S. (2014). Context–based Ontology–driven Recommendation Strategies for Tourism in Ubiquitous Computing. Wireless Personal Communications (Springer), 76(4), 731–745. IF(2015): 0.701
• Chang Choi, Miyoung Cho, Junho Choi, Myunggwon Hwang, Jongan Park, Pankoo Kim, (2009) “Travel Ontology for Intelligent Recommendation System”, 2009 Third Asia International Conference on Modelling & Simulation (AMS), pp.637–642.
• Park, H., Yoon, A., & Kwon, H. C. (2012). Task model and task ontology for intelligent tourist information service. International Journal of u–and e–Service, Science and Technology, 5(2), 43–58.
• Heum Park; Soonho Kwon; Hyuk–Chul Know (2009) "Ontology–based approach to intelligent Ubiquitous Tourist Information System", In Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications (ICUT 09), pp.1–6. 
• Naccarato, G., Pantano, E., & Tavernise, A. (2011). Educational Personalized Contents in a Web Environment: The Virtual Museum Net of Magna Graecia. In Handbook of research on technologies and cultural heritage: Applications and environments (pp. 446–460). IGI Global.
• Park, H. (2013). Task Model and Task Ontology based on Mobile Users’ Generic Activities for Task–Oriented Tourist Information Service. International Journal of Smart Home, 7(3), 33–44.
• Albuquerque, M. D. O., Siqueira, S. W. M., & Braz, M. H. L. B. (2013). Cataloguing and searching musical sound recordings in an Ontology–Based Information System. In Governance, Communication, and Innovation in a Knowledge Intensive Society (pp. 292–306). IGI Global.
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• Moutinho, L., Caber, M., Silva, M. M. S., & Albayrak, T. (2015). Impact of Group Package Tour Dimensions on Customer Satisfaction (an ANNs Application). Tourism Analysis (Cognizant), 20(6), 619–629.
• Alhazbi, S., Lotfi, L., Ali, R., & Suwailih, R. (2013, October). Ontology–based model in tourism context–aware systems. In ICT Convergence (ICTC), 2013 International Conference on (pp. 775–779). IEEE.
• García, J., García–Peñalvo, F. J., & Therón, R. (2012). Through the data modelling process of turimov, an ontology–based project for mobile intelligent systems. In Highlights on Practical Applications of Agents and Multi–Agent Systems (pp. 77–84). Springer Berlin Heidelberg.
• Alhazbi, S., Lotfi, L., Ali, R., & Suwailih, R. (2013, December). An Ontology–Based Context–Aware Mobile System for On–the–Move Tourists. In Evolving Ambient Intelligence: AmI 2013 Workshops, Dublin, Ireland, December 3–5, 2013. Revised Selected Papers (Vol. 413, p. 252). Springer.
• Wicha, S., Temdee, P., & Suebsombut, P. (2014, December). Opened Pins Recommendation System to promote tourism sector in Chiang Rai Thailand. In Asia–Pacific Signal and Information Processing Association, 2014 Annual Summit and Conference (APSIPA) (pp. 1–4). IEEE.
• Colomo–Palacios, R. (2013). Semantic Technologies in Motion: From Factories Control to Customer Relationship Management. In Industrial Engineering: Concepts, Methodologies, Tools, and Applications (pp. 477–498). IGI Global.
• Cabanas–Abascal, A., Rodríguez–González, A., Casado–Lumbreras, C., Fernández–González, J., & Jiménez–López, D. (2013). POST–VIA: Develop Individualized Marketing Strategies for Tourists. In Electronic Business and Marketing (pp. 29–42). Springer Berlin Heidelberg.
• Lin, H. (2013). Personalised e–customer relationship management models and system (Doctoral dissertation).

Kanellopoulos D. (2011) How can teleworking be pro-poor?. Journal of Enterprise Information Management (Emerald), 24(1), 8-29. [Emerging Sources Citation Index (Thomson Reuters)]

• Gálvez, A., Tirado, F., & Jesús Martínez, M. (2020). Work–Life Balance, Organizations and Social Sustainability: Analyzing Female Telework in Spain. Sustainability (MDPI), 12, 3567. DOI:10.3390/su12093567. IF (2019): 2.592
• Spyridakis, M. (2020). COVID-19: Full Teleworking in Greece. Edited by Giuliana B. Prato, 64, 56.
• Queiroga, Fabiana (Editor). Home office guidelines in the COVID–19 pandemic [electronic form]. Brasília: SBPOT Publications, 2020 (Collection: Work and containment measures for COVID–19: contributions from Work and Organizational Psychology in the pandemic context).
• Turan, S. G. (2020). The Relationship Between Technoference, Work-Family Interface, and Telework in the Age of 4IR. In Future of Work, Work-Family Satisfaction, and Employee Well-Being in the Fourth Industrial Revolution (pp. 279-296). IGI Global.
• Roberts, S. C., Smith–Doerr, L., Zilberstein, S., Renski, H., Branch, E. H., & Wilkerson, T. (2019). 13 Automation, Work, and Racial Equity. Advancing Diversity, Inclusion, and Social Justice Through Human Systems Engineering, 191.
•  Morrison, J., Chigona, W., & Malanga, D. F. (2019, September). Factors that Influence Information Technology Workers' Intention to Telework: A South African Perspective. In Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 (p. 32). ACM.
• Ansong, E., & Boateng, R. (2018). Organisational adoption of telecommuting: Evidence from a developing country. The Electronic Journal of Information Systems in Developing Countries (Wiley), 84(1), e12008.
• Jose, S., Jose, S., Chacko, J., & Chacko, J. (2017). Sustainable development of microfinance customers: An empirical investigation based on India. Journal of Enterprise Information Management (Emerald), 30(1), 49–64.
• Boell, S. K., Cecez‐Kecmanovic, D., & Campbell, J. (2016). Telework paradoxes and practices: the importance of the nature of work. New Technology, Work and Employment (Wiley), 31(2), 114–131. Impact Factor (2015): 1.281
• Karia, N., & Asaari, M. H. A. H. (2016). Innovation capability: the impact of teleworking on sustainable competitive advantage. International Journal of Technology, Policy and Management (Inderscience), 16(2), 181–194.
• Skvarciany, V., & Tereštšenkov, J. (2016). Quality of life: interface between cultural specificities and social progress. KSI Transactions on Knowledge Society: a publication of the Knowledge Society Institute, 50–53.
• Tahavori, Z. (2015). Teleworking in the National Library and Archives of Iran: Teleworkers’ attitudes. Journal of Librarianship and Information Science (SAGE), 47(4), 341–355. Impact Factor (2015): 1.239
• Gamal Aboelmaged, M., & Mohamed El Subbaugh, S. (2012). Factors influencing perceived productivity of Egyptian teleworkers: an empirical study. Measuring Business Excellence (Emerald), 16(2), 3–22. [Emerging Sources Citation Index]
• Maree, Johann and Piontak, Rachel and Omwansa, Tonny and Shinyekwa, Isaac and Njenga, Kamotho, Developmental Uses of Mobile Phones in Kenya and Uganda (September 10, 2013). Available at SSRN: https://ssrn.com/abstract=2323429 or https://dx.doi.org/10.2139/ssrn.2323429
• Böll, S., Cecez–Kecmanovic, D., & Campbell, J. (2014). Telework and the nature of work: An assessment of different aspects of work and the role of technology. The 22nd European Conference on Information Systems (ECIS 2014) Tel Aviv, Israel. 9–11 June 2014
• Boell, S. K., Campbell, J., Cecez–Kecmanovic, D., & Cheng, J. E. (2013). The Transformative Nature of Telework: A Review of the Literature. Telework: Advantages, Challenges and Contradictions. Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15–17, 2013
• Campbell, J., Boell, S., Keating, B., & Cecez–Kecmanovic, D. (2013). Temporal aspects of telework and its impact on work–family conflict. In Australasian Conference on Information Systems 2013.
• Mekonnen, T. (2013). Examining the effect of teleworking on employees' job performance (Doctoral dissertation, Walden University).
• Cheuk, S., Atang, A., & Lo, M. C. (2012). Community attitudes towards the telecentre in Bario, Borneo Malaysia: 14 years on. International Journal of Innovation, Management and Technology, 3(6), 682.
• Vonhof, J. J. (2015). Middle management and telework adoption: Development of an instrument using Delphi and exploratory factor analysis for the financial services industry (Doctoral dissertation, Capella University).
• Scott, G. (2014). Big Broadband: One Component of a Complex System.
• Yinat, J. (2014). Relationship of management performance practices on telework resistance outcomes in the US federal government (Doctoral dissertation, Capella University).
• Böll, S., Cecez–Kecmanovic, D., & Campbell, J. (2014). Telework and the nature of work: An assessment of different aspects of work and the role of technology.
•  Cradduck, L. M. (2013). Mobile valuations: the Internet's impact on traditional valuation services.
• ABOELMAGED, M. G., & ELSUBBAUGH, S. M. Boosting Teleworking Productivity in Egypt: An Empirical Examination of Technology, Organizational and Individual Determinants.

Kanellopoulos D. (2009) ODELO: An ontology-driven model for the evaluation of learning ontologies. International Journal of Learning Technology (Inderscience), 4(1/2): 73-99. [Emerging Sources Citation Index]

• Gintare Grigonyte (2010) Chapter 5: NLP and Ontology evaluation. In Building and Evaluating Domain Ontologies: NLP Contributions, Logos Verlag Berlin GmbH, 2010 – 214 pages.
• K.R. Uthayan and G.S. Anandha Mala (2010) A survey on designing metrics suite to asses the quality of ontology. International Journal of Computer Science and Information Security, Vol. 8, No. 8, pp.179–184.

Kanellopoulos D. and Kotsiantis S. (2008) Towards an ontology-based system for intelligent prediction of students dropouts in Distance Learning. International Journal of Management in Education (Inderscience), 2(2):172-194.

• Kosir, S. (2009). Study support as students' motivation for study. International Journal of Management in Education, 4(1), 25–45.
• Vo, T. N. C., & Nguyen, H. P. (2012, February). A knowledge–driven educational decision support system. In Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2012 IEEE RIVF International Conference on (pp. 1–6). IEEE.
• Chau, V. T. N., & Phung, N. H. (2013, November). Imbalanced educational data classification: an effective approach with resampling and random forest. In Computing and Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), 2013 IEEE RIVF International Conference on (pp. 135–140). IEEE.
• Kasimati, A., & Zamani, E. (2011, September). Education and learning in the semantic web. In Informatics (PCI), 2011 15th Panhellenic Conference on (pp. 338–344). IEEE.
• Levashenko, V., Zaitseva, E., Kostolny, J., & Kvassay, M. (2015, November). Educational portal with data mining support based on modern technologies. In Emerging eLearning Technologies and Applications (ICETA), 2015 13th International Conference on (pp. 1–6). IEEE.
• Paiva, R., Borges, D., Santos, J., Bittencourt, I. I., & da Silva, A. P. (2014, March). Lessons learned from an online open course: a Brazilian case study. In Proceedings of the 29th Annual ACM Symposium on Applied Computing (pp. 229–234). ACM.

Kanellopoulos D. and Kotsiantis S. (2007) Semantic web: A state of the art survey. International Review on Computers and Software, 2(4), 428-442.

• Shah, A. A., Ravana, S. D., Hamid, S., & Ismail, M. A. (2015). Web credibility assessment: Affecting factors and assessment techniques. Information Research (ISSN: 1368–1613), 20(1), 20–1. ISI Indexed.
• Qingyu Zhang and Richard S. Segall (2008). Web mining: A survey of current research, techniques, and software. International Journal of Information Technology & Decision Making (World Scientific), 7(4), 683–720. Impact Factor (2015): 1.183
• Kalidoss, K., & Vajravelu, K. (2014). PROCEOL: Probabilistic relational of concept extraction in ontology learning. International Review on Computers and Software (IRECOS), 9(4), 716–726.
• Alifard, A., Shadgar, B., & Osareh, A. (2011). An Experimental Observation–based Ontology Evolution Framework. International Review on Computers and Software, 6(5), 827–833.
• Inma Rodrriguez–Ardura, Francisco J. Martinez–LOpez, Antoni Meseguer Artola (2008) The Online power game: Marketing strategies to manage the enhanced consumer's empowerment. IADIS eCommerce 2008, pp.144–150.
• Dominic Mainz (2008) “Deep integration of the OWL ontology language into Ruby using metaprogramming”. PhD Dissertation. [Online:] https://docserv.uni–duesseldorf.de/servlets/DerivateServlet/Derivate–10799/DominicMainz.pdf

Lazarinis F., Kanellopoulos D. and Lalos, P. (2008) Heuristically evaluating Greek e-tourism and e-museum websites.  Electronic Journal on Information Systems Evaluation (EJISE), Vol. 11, Issue 1, pp.17-26.

• Kiourexidou, M., Antonopoulos, N., Kiourexidou, E., Piagkou, M., Kotsakis, R., & Natsis, K. (2019). Websites with Multimedia Content: A Heuristic Evaluation of the Medical/Anatomical Museums. Multimodal Technologies and Interaction (MDPI), 3(2), 42.
• Kabassi, K., Maravelakis, E., & Konstantaras, A. (2018). Heuristics and Fuzzy Multi–Criteria Decision Making for Evaluating Museum Virtual Tours. International Journal of the Inclusive Museum, 11(3), 1–21. doi:10.18848/1835–2014/CGP/v11i03/1–21.
• Kabassi, K. (2017). Evaluating websites of museums: State of the art. Journal of Cultural Heritage (Elsevier), 24, 184–196. IF (2015): 1.533
• Parker, C., Fraunholz, B., Zutshi, A., & Crofts, M. (2011). How do Australian small and medium enterprises communicate their environmental improvement activities online?. Australasian Journal of Information Systems, 17(1) pp.5–21.
• Gomaa, H. A. A., & Yousef, M. A. (2016). Exploring the Features of Digital Cultural Heritage Tourism, Egyptian E–museums: Case Study. Journal of Faculty of Tourism and Hotels, Fayoum University, 8(1).
• Lončarić, D., Bašan, L., & Sinkovič, L. (2014, January). Museum Websites Content as a Mean for Cultural Heritage Promotion and Attracting Visitors: The Case of Istria. In 6th International Conference on Applied Economics, Business and Development (AEBD'14).
• Lončarić, D., Prodan, M. P., & Ribarić, I. (2016). THE INFLUENCE OF A VISITOR’S PERCEPTIONS OF A MUSEUM’S WEBSITE DESIGN ON BEHAVIOURAL INTENTIONS. Ekonomski vjesnik/Econviews–Review of Contemporary Business, Entrepreneurship and Economic Issues, 29(1), 65–79.
• Kaur, M., & Sharma, N. (2015). Information technology applications in tourism and hospitality: critical analysis of empirical evidences from 1999–2013. Abhigyan, 33(1), 59–75.
• Horvath, Z., Kraushofer, A., Pok, E., & Wedl, S. (2015, April). The Digital Divide and User Experience of Blind and Visually Impaired Tourists. In ISCONTOUR 2015–Tourism Research Perspectives: Proceedings of the International Student Conference in Tourism Research (p. 137). BoD–Books on Demand.
• Sorkowska–Cieślak, K., & Cieślak, M. (2016). ENGLISH ON POLISH MUSEUMS’WEBSITES: STANDARD OR EXCEPTION. Państwo i Społeczeństwo, 151.
• Parker, C. M., Zutshi, A., Fraunholz, B., & Crofts, M. R. (2012). A method for examining SME descriptions of environmental sustainability online. Green Technologies and Business Practices: An IT Approach: An IT Approach, 15.
• Kaur, M., & Sharma, N. (2015). State tourism websites in India: A comparative study. BUSINESS REVIEW (GBR), 67.
• Horvath, Z., Kraushofer, A., Pok, E., & Wedl, S. (2015, April). The Digital Divide and User Experience of Blind and Visually Impaired Tourists. In ISCONTOUR 2015–Tourism Research Perspectives: Proceedings of the International Student Conference in Tourism Research (p. 137). BoD–Books on Demand.

Tiropanis T. and Kanellopoulos D. (2008) “A schema-based P2P network to enable publish-subscribe for multimedia content in Open Hypermedia Systems”, International Journal of Web Engineering and Technology (Inderscience Publishers), Vol. 4, No. 1, pp.21–43.

• Dong, B. (2013). Architecting Multimedia Content Publish/Subscribe Applications: A Graph-Oriented Approach. In Applied Mechanics and Materials (Vol. 336, pp. 1964-1967). Trans Tech Publications.

Kanellopoulos D. (2007) “eTourism services and technologies: Current issues and trends”, Tourism Issues, No. 1, pp.4-17.

• Pitoska, E. (2013). E-tourism: The use of internet and information and communication technologies in tourism: The case of hotel units in peripheral areas.
• Amoako, G. K., Adjaison, G. K., Kumi, D. K., & Asamoah, F. K. (2015). Using MIS for Strategic Planning and Management Control in Tourism Industries. In New Business Opportunities in the Growing E-Tourism Industry (pp. 20-42). IGI Global.

Kanellopoulos D., Sakkopoulos E., Lytras M. and Tsakalidis A. (2007) Using web-based teaching interventions in computer science courses. IEEE Transactions on Education, 50(4): 338-344. ISI Impact Factor (2015): 1.33

• Wyne, M. F., AG, A. A. G., & Akhtar, S. (2017, June). IT–based Solution to Foster Student Engagement. In 2017 ASEE Annual Conference & Exposition.
• E. Sakkopoulos, C. Costopoulou, M. Ntaliani, A. Liopa–Tsakalidis, A. Sideridis (2011) An Architecture of m–Learning Environment for Medicinal and Aromatic Plants. Journal of Information Technology in Agriculture, Vol. 4, No.1
• Kai Pan, Mark Douglas, R. Vogel (2009) “An Exploratory Study of Personalization and Learning Systems Continuance”. Pacific Asia Conference on Information Systems (PACIS). Paper 34, https://aisel.aisnet.org/pacis2009/34
• Banhaddou, D. Mickelson, A.R. (2009) Assessment or remote “optical circuits” laboratory using embedded measurement techniques. 2009 ASEE Annual Conference and Exposition, Conference Proceedings.
• Mark K.P. and Vogel D. (2009) Technology support for engagement retention: The case of BackPack. Knowledge Management & E–Learning: An International Journal (KM&EL), Vol. 1, No. 3, pp.163–178.
• Maria Vargas–Vera and Miltiadis D. Lytras (2008) Exploiting semantic web and ontologies for personalised learning services: Towards semantic web–enabled learning portals for real learning experiences. International Journal of Knowledge and Learning (Inderscience), Vol. 4, No. 1, pp.1–17.
• M. Lytras and R. Garcia (2008) Semantic Web applications: A framework for industry and business exploitation––What is needed for the adoption of the Semantic Web from the market and industry. International Journal of Knowledge and Learning (Inderscience), Vol. 4, No. 1, pp.93–108.
• Han J., Hu W. and Feng X. (2008) Exploration and practice on teaching java as introductory language for non–CSE major students. Proceedings of the 9th IEEE Int.l Conference for Young Computer Scientists (ICYCS 2008), pp.2696 2700.
• Oginga, R. A., & Karie, N. M. (2014). Evaluating Moodle As An Open Source E–Learning Software Tools For Teaching In Tertiary Institutions. International Journal of Advanced Research in Computer Science, 5(7).
• Sakkopoulos E. (2007) “Semantic technologies for mobile Web”. 2nd International Conference on Metadata and Semantics Research, Corfu, Greece 11–12 October 2007, post–proceedings published by Springer.

Lazari C. and Kanellopoulos D. (2007) Total Quality Management in hotel restaurants: a case study in Greece. International Journal of Engineering and Applied Sciences, 2(3), 564-571.

• Bazazo, I., Alansari, I., Alquraan, H., Alzgaybh, Y., & Masa’deh, R. E. (2017). The Influence of Total Quality Management, Market Orientation and E–Marketing on Hotel Performance. International Journal of Business Administration, 8(4), 79.
• Cheng–Hua Wang, Kuan–Yu Chen and Shiu–Chun Chen (2012) Total quality management, market orientation and hotel performance: The moderating effects of external environmental factors. International Journal of Hospitality Management (Elsevier), 31(1), 119–129. IF (2015): 2.061
• Talib, F., Rahman, Z., & Qureshi, M. N. (2012). Total quality management in service sector: a literature review. International Journal of Business Innovation and Research, 6(3), 259–301.
• Wang, C. H., Chen, S. C., & Chen, K. Y. (2011). Using fuzzy cognitive map and structural equation model for market–oriented hotel and performance. African Journal of Business Management, 5(28), 11358.
• Camisón, C., Puig‐Denia, A., Forés, B., Fabra, M. E., Muñoz, A., & Muñoz Martínez, C. É. S. A. R. (2016). The importance of internal resources and capabilities and destination resources to explain firm competitive position in the Spanish tourism industry. International Journal of Tourism Research, 18(4), 341–356.
• Nancy Bouranta, Evangelos L. Psomas, Angelos Pantouvakis, (2017). Identifying the critical determinants of TQM and their impact on company performance: Evidence from the hotel industry of Greece", The TQM Journal, Vol. 29 Issue: 1, pp.147–166.

Kanellopoulos D. and Kotsiantis S. (2007) “Wireless multimedia communications impacts on tourism destination value chain”, Journal of Engineering and Applied Sciences, Vol. 2, No. 1, pp.161-169.

• Goncalo Jorge Morais de Costa, Nuno Sotero Alves da Silva, Piotr Pawlak (2010) Network Tourism: A Fallacy of Location Privacy. ETHICOMP 2010, Rovira I Virgili University Spain, 14-16 April, 2010.

Kanellopoulos D. and Kotsiantis S. (2007) A semantic-based architecture for intelligent destination management systems. International Journal of Soft Computing, 2(1): 61-68.

• Alti, A., Boukerram, A., & Roose, P. (2013). Ontology and tool support for quality service management. Journal of Systems and Information Technology (Emerald), 15(1), 4-23.
• Alti, A., Boukerram, A., & Roose, P. (2012). Selector: A tool for dynamic service selection and management. Journal of Computing, 4(4), 23-32.
• Adel, A., & Abbdellah, B. (2010, October). CxQWS: Context-aware Quality Semantic Web Service. (ICMWI), 2010 IEEE International Conference on Machine and Web Intelligence (pp. 69-76).
• M. Thangaraj, R. Somasundara Manikanda (2011) “A Survey on Semantic Web Based E-Tourism Dynamic Package”, International Journal of Computer Science and Information Technologies, 2(2), 611-613.

Kanellopoulos D. and Kotsiantis S. (2006) Towards intelligent wireless web services for Tourism. International Journal of Computer Science and Network Security, 6(7B): 83-90. [ESCI]

• Gong, Y. (2017). 11. Research on the Game between Public Service Platform for All-for-one Tourism and Demand Side of Tourism Service. Boletín Técnico, ISSN: 0376-723X, 55(10).
• Samir A. El-Seoud and Hosam F. El-Sofany (2010) “Mobile Tourist Guide – An Intelligent Wireless System to Improve Tourism, using Semantic Web”. CONFERENCE ICL 2010. SEPTEMBER 15 -17, 2010 HASSELT, BELGIUM.
• Damljanovic, D., Devedzic, V. (2009) Semantic Web and e-tourism. In Mehdi Khosrow-Pour (Ed.) Encyclopedia of Information Science and Technology, Vol. VII, 2^nd Ed., IGI Global, Hershey, PA, 2009, pp.3426-3432.
• Yu Maw, Soe and Lar Thein, Ni. (2009) Multi-Agent Mobile Tourism System. In Mehdi Khosrow-Pour (Ed.) Encyclopedia of Information Science and Technology. 2nd Ed., IGI Global, Hershey, PA, 2009, pp.2722-2727.
• Danica Damljanovic (2007) Intelligent Web portal in the area of Tourism. Department of Information Systems, University of Belgrade, Serbia. (MSc Information Systems- Supervisor: Prof. Vladan Devedzic).

[J17]  Kotsiantis S. and Kanellopoulos D. (2006) Discretization techniques: A recent survey. GESTS International Transactions on Computer Science and Engineering, 32(1): 47-58. ISSN: 1738-6438.

• Fasaee, M. A. K., Berglund, E., Pieper, K. J., Ling, E., Benham, B., & Edwards, M. (2021). Developing a framework for classifying water lead levels at private drinking water systems: A Bayesian Belief Network approach. Water Research (Elsevier), 189, 116641.
• Sreeparvathy, V., & Srinivas, V. V. (2020). A fuzzy entropy approach for design of hydrometric monitoring networks. Journal of Hydrology (Elsevier), 124797.IF: 4.500
• Phillips, P., Antonio, N., de Almeida, A., & Nunes, L. (2020). The influence of geographic and psychic distance on online hotel ratings. Journal of Travel Research (SAGE), 59(4), 722–741.
• Barman, B., & Patra, S. (2020). Variable precision rough set based unsupervised band selection technique for hyperspectral image classification. Knowledge–Based Systems (Elsevier), 193, 105414. IF:5.921
• Zhao, Y., Zhu, W., Yang, M., & Wang, M. (2020). Bayesian Network Based Imprecise Probability Estimation Method for Wind Power Ramp Events. Journal of Modern Power Systems and Clean Energy (Springer). IF:3.090
• Das, A., & Patra, S. (2020). A rough–GA based optimal feature selection in attribute profiles for classification of hyperspectral imagery. Soft Computing (Springer), 1–17. IF:3.050
• Zhang, L., Ray, H., Priestley, J., & Tan, S. (2020). A descriptive study of variable discretization and cost–sensitive logistic regression on imbalanced credit data. Journal of Applied Statistics, 47(3), 568–581. IF:1.031
• Bain, T. C., Avila–Herrera, J. F., Subasi, E., & Subasi, M. M. (2020). Logical analysis of multiclass data with relaxed patterns. Annals of Operations Research (Springer), 287(1), 11–35. IF:2.583
• Tsai, C. F., & Chen, Y. C. (2019). The optimal combination of feature selection and data discretization: An empirical study. Information Sciences (Elsevier), 505, 282–293. IF: 5.910
• Mutlu, A., Göz, F. U. R. K. A. N., & Akbulut, O. (2019). IFIT: an unsupervised discretization method based on the Ramer–Douglas–Peucker algorithm. Turkish Journal of Electrical Engineering & Computer Sciences, 27(3), 2344–2360. IF:0.702
• Drchal, J., Čertický, M., & Jakob, M. (2019). Data–driven activity scheduler for agent–based mobility models. Transportation Research Part C: Emerging Technologies, 98, 370–390. IF: 3.968
• Shabani, A., Visani, F., Barbieri, P., Dullaert, W., & Vigo, D. (2019). Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights. Omega (Elsevier), 87, 57–70. IF:5.341
• Cotfas, D. T., Deaconu, A. M., & Cotfas, P. A. (2019). Application of successive discretization algorithm for determining photovoltaic cells parameters. Energy conversion and management, 196, 545–556.
• Cózar, J., Marcelloni, F., Gámez, J. A., & de la Ossa, L. (2018). Building efficient fuzzy regression trees for large scale and high dimensional problems. Journal of Big Data, 5(1), 49.
• Segatori, A., Marcelloni, F., & Pedrycz, W. (2018). On distributed fuzzy decision trees for big data. IEEE Transactions on Fuzzy Systems, 26(1), 174–192. IF:9.518
• Herrera–Vega, J., Orihuela–Espina, F., Ibargüengoytia, P. H., García, U. A., Morales, E. F., & Sucar, L. E. (2018). A local multiscale probabilistic graphical model for data validation and reconstruction, and its application in industry. Engineering Applications of Artificial Intelligence, 70, 1–15. IF:4.201
• Diab, D. M., & El Hindi, K. (2018). Using differential evolution for improving distance measures of nominal values. Applied Soft Computing (Elsevier), 64, 14–34. IF:5.472
• Yang, D. Y., & Frangopol, D. M. (2018). Probabilistic optimization framework for inspection/repair planning of fatigue–critical details using dynamic Bayesian networks. Computers & Structures (Elsevier), 198, 40–50. IF:3.664
• Hacibeyoglu, M., & Ibrahim, M. H. (2018). EF_Unique: An Improved Version of Unsupervised Equal Frequency Discretization Method. Arabian Journal for Science and Engineering, 1–10.
• Casanova, I. J., Campos, M., Juarez, J. M., Fernandez–Fernandez–Arroyo, A., & Lorente, J. A. (2018). Impact of time series discretization on intensive care burn unit survival classification. Progress in Artificial Intelligence (Springer), 7(1), 41–53. [ESCI]
• Ma, C. W., & Ma, Y. G. (2018). Shannon information entropy in heavy-ion collisions. Progress in Particle and Nuclear Physics (Elsevier), 99, 120-158.
• Yang, H., & Cheung, L. P. (2017). Implicit Heterogeneous Features Embedding in Deep Knowledge Tracing. Cognitive Computation, 1–12. IF(2016): 3.441
• Khanmohammadi, S. (2017). An improved synchronization likelihood method for quantifying neuronal synchrony. Computers in Biology and Medicine (Elsevier). IF(2016): 1.836
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• Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2017). Feature selection: A data perspective. ACM Computing Surveys (CSUR), 50(6), 1-45.
• Tran, B., Xue, B., & Zhang, M. (2017). A new representation in PSO for discretization-based feature selection. IEEE Transactions on Cybernetics, 48(6), 1733-1746.
• Segatori, A., Marcelloni, F., & Pedrycz, W. (2017). On distributed fuzzy decision trees for big data. IEEE Transactions on Fuzzy Systems, 26(1), 174-192.
• Bechini, A., Marcelloni, F., & Segatori, A. (2016). A MapReduce solution for associative classification of big data. Information Sciences (Elsevier), 332, 33-55.
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• Lin, L., Wang, Q., & Sadek, A. W. (2015). A novel variable selection method based on frequent pattern tree for real-time traffic accident risk prediction. Transportation Research Part C: Emerging Technologies (Elsevier), 55, 444-459.
• Frayer, J., Sun, Z., Müller, D., Munroe, D. K., & Xu, J. (2014). Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks. Land use policy (Elsevier), 36, 248-258.
•  Herman, G., Zhang, B., Wang, Y., Ye, G., & Chen, F. (2013). Mutual information-based method for selecting informative feature sets. Pattern Recognition (Elsevier), 46(12), 3315-3327.
• Peters, F., Menzies, T., Gong, L., & Zhang, H. (2013). Balancing privacy and utility in cross-company defect prediction. IEEE Transactions on Software Engineering, 39(8), 1054-1068.
• Neshatian, K., Zhang, M., & Andreae, P. (2012). A filter approach to multiple feature construction for symbolic learning classifiers using genetic programming. IEEE Transactions on Evolutionary Computation, 16(5), 645-661.
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• A. Cecchinato, M. Penasa, M. De Marchi, L. Gallo, G. Bittante and P. Carnier (2011) Genetic parameters of coagulation properties, milk yield, quality, and acidity estimated using coagulating and noncoagulating milk information in Brown Swiss and Holstein–Friesian cows. Journal of Dairy Science (Elsevier), 94(8), 4205–4213. IF(2015): 2.408
• Feras Al–Obeidat, Nabil Belacel (2011) Alternative approach for learning and improving the MCDA method PROAFTN. International Journal of Intelligent Systems (Wiley), 26(5), 444–463. IF(2015): 2.05
• Tae Young Yang (2009). Efficient multi–class cancer diagnosis algorithm, using a global similarity pattern. Computational Statistics & Data Analysis (Elsevier), 53(3), 756–765. Impact Factor (2015): 1.179
• Mahnhoon Lee, Witold Pedrycz (2009) Adaptive learning of ordinal–numerical mappings through fuzzy clustering for the objects of mixed features. Fuzzy Sets and Systems (Elsevier), 161(4), 564–577. IF: 2.098
• Kronek, L–P., Reddy A. (2008) Logical analysis of survival data: prognostic survival models by detecting high–degree interactions in right–censored data. Bioinformatics (Oxford Journals) 24(16), pp. i248–i253. IF: 5.766
• A Singh, J Liu, JV Guttag (2010) Discretization of Continuous ECG based Risk Metrics Using Asymmetric and Warped Entropy Measures. 2010 IEEE Computing in Cardiology, Vol. 37, pp. 473−476.
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• Yi Gao; Chun Chen; Jiajun Bu; Wei Dong; Daojing He (2011) “ICAD: Indirect correlation based anomaly detection in dynamic WSNs”, In 2011 IEEE Wireless Communications and Networking Conference (WCNC), pp.647–652. Cancun, Quintana Roo. 28–31 March 2011.
• Olympia Roeva and Tsonyo Slavov (2011) “Fed–Batch Cultivation Control Based on Genetic Algorithm PID Controller Tuning. Numerical Methods and Applications”. Lecture Notes in Computer Science, 2011, Volume 6046/2011, 289–296, DOI: 10.1007/978–3–642–18466–6_34.
• Rajashree Dash, Rajib Lochan Paramgurn, Rasmita Dash (2011) “Comparative analysis of supervised and unsupervised discretization techniques”, International Journal of Advances in Science and Technology, Vol. 2, No. 3.
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• Rajashree Dash, Rasmita Dash, and Debahuti Mishra (2010) “A hybridized rough–PCA approach of attribute reduction for high dimensional data set”, European Journal of Scientific Research, ISSN 1450–216X, Vol. 44 No. 1, pp.29–38.
• Andrea Esuli and Fabrizio Sebastiani (2009) “Encoding Ordinal Features into Binary Features for Text Classification”. M. Boughanem et al. (Eds.): ECIR 2009, LNCS 5478, pp. 771–775, 2009. Springer–Verlag Berlin Heidelberg 2009.
• LiangChi Wang, “Classification Rule Discovery with Particle Swarm Optimization”, Master Thesis, Department of Information Management, National Kaohsiung First University of Science and Technology.
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• Singh, H., Grover, P., Kar, A. K., & Ilavarasan, P. V. (2020). Review of performance assessment frameworks of e–government projects. Transforming Government: People, Process and Policy.
• Ferri–García, R., Fernández–Luna, J. M., Rodríguez–López, C., & Chillón, P. (2020). Data mining techniques to analyze the factors influencing active commuting to school. International journal of sustainable transportation, 14(4), 308–323.
• Grabot, B. (2020). Rule mining in maintenance: analysing large knowledge bases. Computers & Industrial Engineering. 139, 105501. ISI Impact Factor (2017):  3.195
• Al–Garadi, M. A., Mohamed, A., Al–Ali, A., Du, X., Ali, I., & Guizani, M. (2020). A survey of machine and deep learning methods for internet of things (IoT) security. IEEE Communications Surveys & Tutorials.
• Tahsien, S. M., Karimipour, H., & Spachos, P. (2020). Machine learning based solutions for security of Internet of Things (IoT): A survey. Journal of Network and Computer Applications, 102630.
• Genga, L., Zannone, N., & Squicciarini, A. (2019). Discovering Reliable Evidence of Data Misuse by Exploiting Rule Redundancy. Computers & Security (Elsevier), 101577. Impact Factor: 3.062
• Sun, C., Zhang, R., Sharples, S., Han, Y., & Zhang, H. (2018). Thermal comfort, occupant control behaviour and performance gap–A study of office buildings in north–east China using data mining. Building and Environment. Impact Factor: 4.539
• Breuer, R., Mattheisen, M., Frank, J., Krumm, B., Treutlein, J., Kassem, L., ... & Cichon, S. (2018). Detecting significant genotype–phenotype association rules in bipolar disorder: market research meets complex genetics. International Journal of Bipolar Disorders, 6(1), 24.
• Jayashree, R., Christy, A., & Venkatesh, S. (2018). Personalised recommendation system for ranking in question–answering websites with splay tree by avoiding tumbleweed badge. International Journal of Trust Management in Computing and Communications, 4(2), 172–191.
• Samoilenko, S., & Osei–Bryson, K. M. (2018). A Data Analytic Benchmarking Methodology for Discovering Common Causal Structures that Describe Context–Diverse Heterogeneous Groups. Expert Systems with Applications. ISI Impact Factor (2015):  2.981
• Bhardwaj, S., Saxena, A., & Nayyar, A. (2018). Exploratory Data Analysis on Hard Drive Failure Statistics and Prediction. International Journal, 6(6).
• Wang, H., Dauod, H., Khader, N., Yoon, S. W., & Srihari, K. (2018). Multi–objective parallel robotic dispensing planogram optimisation using association rule mining and evolutionary algorithms. International Journal of Computer Integrated Manufacturing, 1–16.
• Di Corso, E., Cerquitelli, T., & Apiletti, D. (2018). METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self–Learning Transparent Models. Energies, 11(6), 1336.
• Yang, C. C., & Yang, H. (2018). Mining heterogeneous networks with topological features constructed from patient–contributed content for pharmacovigilance. Artificial intelligence in Medicine, 90, 42–52.
• Damangir, S., Du, R. Y., & Hu, Y. (2018). Uncovering Patterns of Product Co–consideration: A Case Study of Online Vehicle Price Quote Request Data. Journal of Interactive Marketing, 42, 1–17.
• Heinrich, B., Klier, M., Schiller, A., & Wagner, G. (2018). Assessing data quality–A probability–based metric for semantic consistency. Decision Support Systems. Impact Factor: 3.565
• Piri, S., Delen, D., Liu, T., & Paiva, W. (2018). Development of a new metric to identify rare patterns in association analysis: The case of analyzing diabetes complications. Expert Systems with Applications, 94, 112–125. ISI Impact Factor (2015):  2.981
• Valle, M. A., Ruz, G. A., & Morrás, R. (2018). Market basket analysis: Complementing association rules with minimum spanning trees. Expert Systems with Applications, 97, 146–162. ISI Impact Factor (2015):  2.981
• Faridi, M., Verma, S., & Mukherjee, S. (2018). Integration of GIS, Spatial Data Mining, and Fuzzy Logic for Agricultural Intelligence. In Soft Computing: Theories and Applications (pp. 171–183). Springer, Singapore.
• Stewart, B., & Khare, A. (2018). Athabasca university reduces ICT carbon footprint. GSTF Journal on Computing (JoC), 1(4).
• Nachida, D. R., Fahima, N., & Fatima, B. (2018). A new approach to supporting runtime decision making in mobile OLAP. International Journal of Information and Communication Technology, 13(2), 149–175.
• Fan, C., Xiao, F., Li, Z., & Wang, J. (2017). Unsupervised Data Analytics in Mining Big Building Operational Data for Energy Efficiency Enhancement: A Review. Energy and Buildings.
• Mao, Z., Jiang, Y., Min, G., Leng, S., Jin, X., & Yang, K. (2017). Mobile social networks: Design requirements, architecture, and state–of–the–art technology. Computer Communications, 100, 1–19.
• Ghodsi, M. M., & Zandieh, M. (2017). A novel artificial immune system–based approach for mining associative classification rules with stock trading data. International Journal of Innovative Computing and Applications, 8(3), 149–161.
• Grover, P., & Kar, A. K. (2017). Big data analytics: a review on theoretical contributions and tools used in literature. Global Journal of Flexible Systems Management, 18(3), 203–229.
• Alsallakh, B., & Ren, L. (2017). PowerSet: A Comprehensive Visualization of Set Intersections. IEEE Transactions on Visualization and Computer Graphics, 23(1), 361–370. IF(2015): 1.4
• Cerezo, R., Esteban, M., Sánchez–Santillán, M., & Núñez, J. C. (2017). Procrastinating Behavior in Computer–Based Learning Environments to Predict Performance: A Case Study in Moodle. Frontiers in Psychology, 8, 1403.
• Kim, J. W. (2017). Construction and evaluation of structured association map for visual exploration of association rules. Expert systems with applications, 74, 70–81. IF(2015):  2.981
• Ding, Z., Liao, X., Su, F., & Fu, D. (2017). Mining Coastal Land Use Sequential Pattern and Its Land Use Associations Based on Association Rule Mining. Remote Sensing, 9(2), 116.
• Haynes, C., Luck, M., McBurney, P., Mahmoud, S., Vítek, T., & Miles, S. (2017). Engineering the emergence of norms: a review. The Knowledge Engineering Review, 32.
• Kaminskas, M., Bridge, D., Foping, F., & Roche, D. (2017). Product–Seeded and Basket–Seeded Recommendations for Small–Scale Retailers. Journal on Data Semantics, 6(1), 3–14.
• Lin, C. T., Hsieh, T. Y., Liu, Y. T., Lin, Y. Y., Fang, C. N., Wang, Y. K., ... & Chuang, C. H. (2017). Minority Oversampling in Kernel Adaptive Subspaces for Class Imbalanced Datasets. IEEE Transactions on Knowledge and Data Engineering. Impact Factor (2016): 2.476
• Lazarova–Molnar, S., & Mohamed, N. (2019). Collaborative data analytics for smart buildings: opportunities and models. Cluster Computing (Springer), 22(1), 1065–1077. IF:3.458
• Pang, Y., Xue, X., & Namin, A. S. (2017). Fault Localizations Through Feature Selections. International Journal of Software Engineering and Knowledge Engineering, 27(08), 1269–1289.
• Ribeiro, C. E., & Zárate, L. E. (2017). Data Preparation for Longitudinal Data Mining: a case study on human ageing. Journal of Information and Data Management, 7(2), 116.
• Hamidi, H., & Hashemzadeh, E. (2017). An Approach to Improve Generation of Association Rules in Order to Be Used in Recommenders. International Journal of Data Warehousing and Mining (IJDWM), 13(4), 1–18. IF:(2015): 0.727
• Altuntas, S., Dereli, T., & Kusiak, A. (2016). Assessment of corporate innovation capability with a data–mining approach: industrial case studies. Computers & Industrial Engineering (Elsevier), 102, 58–68. IF:3.518
• Paredes–Frigolett, H., & Gomes, L. F. A. M. (2016). A novel method for rule extraction in a knowledge–based innovation tutoring system. Knowledge–Based Systems, 92, 183–199.
• Kart, Ö., Özçelik, G., & Kut, A. (2016). Intelligent Data Analysis on a Cloud for Small and Medium Sized Enterprises. The SIJ Transactions on Computer Science Engineering & its Applications (CSEA), Vol. 4, No. 4, August 2016
• Yan, Z., Xing, M., Zhang, D., & Ma, B. (2015). EXPRS: An extended pagerank method for product feature extraction from online consumer reviews. Information & Management (Elsevier), 52(7), 850–858. IF:(2015): 2.163
• Ting, S. L., Tse, Y. K., Ho, G. T. S., Chung, S. H., & Pang, G. (2014). Mining logistics data to assure the quality in a sustainable food supply chain: A case in the red wine industry. International Journal of Production Economics (Elsevier), 152, 200–209. IF(2015): 2.782
• Chougule, R., Rajpathak, D., & Bandyopadhyay, P. (2011). An integrated framework for effective service and repair in the automotive domain: An application of association mining and case–based–reasoning. Computers in Industry (Elsevier), 62(7), 742–754. IF(2015): 1.685
• Rajpathak, D., Chougule, R., & Bandyopadhyay, P. (2012). A domain–specific decision support system for knowledge discovery using association and text mining. Knowledge and Information Systems (Springer), 31(3), 405–432. IF(2015): 1.702
• Soysal, Ö. M. (2015). Association rule mining with mostly associated sequential patterns. Expert Systems with Applications, 42(5), 2582–2592. IF(2015):  2.981
• Geum, Y., Lee, H., Lee, Y., & Park, Y. (2015). Development of data–driven technology roadmap considering dependency: An ARM–based technology roadmapping. Technological Forecasting and Social Change, 91, 264–279.
• Altuntas, S., Dereli, T., & Kusiak, A. (2015). Analysis of patent documents with weighted association rules. Technological Forecasting and Social Change, 92, 249–262.
• Bhatt, C., & Kankanhalli, M. (2011). Probabilistic temporal multimedia data mining. ACM Transactions on Intelligent Systems and Technology (TIST), 2(2), 17.
• Duneja, E., & Sachan, A. K. (2012). A survey on frequent itemset mining with association rules. International Journal of Computer Applications, 46(23), 18–24.
• Zanin, M., Papo, D., Sousa, P. A., Menasalvas, E., Nicchi, A., Kubik, E., & Boccaletti, S. (2016). Combining complex networks and data mining: why and how. Physics Reports, 635, 1–44.
• Cakir, O., & Aras, M. E. (2012). A recommendation engine by using association rules. Procedia–Social and Behavioral Sciences, 62, 452–456.
• Mangat, V., & Vig, R. (2014). Novel associative classifier based on dynamic adaptive PSO: Application to determining candidates for thoracic surgery. Expert Systems with Applications, 41(18), 8234–8244. ISI Impact Factor (2015):  2.981
• Mangat, V., & Vig, R. (2014). Dynamic PSO–based associative classifier for medical datasets. IETE Technical Review, 31(4), 258–265.
• Lai, J., Li, Y., Deng, R. H., Weng, J., Guan, C., & Yan, Q. (2014). Towards semantically secure outsourcing of association rule mining on categorical data. Information Sciences, 267, 267–286.
• Chandanan, A. K., & Shukla, M. K. (2015). Removal of duplicate rules for association rule mining from multilevel dataset. Procedia Computer Science, 45, 143–149.
• Xun, Y., Zhang, J., & Qin, X. (2016). Fidoop: Parallel mining of frequent itemsets using mapreduce. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(3), 313–325.
• Yang, Y., Liu, H., & Cai, Y. (2013). Discovery of online shopping patterns across websites. INFORMS Journal on Computing, 25(1), 161–176.
• Khader, N., Lashier, A., & Yoon, S. W. (2016). Pharmacy robotic dispensing and planogram analysis using association rule mining with prescription data. Expert Systems with Applications, 57, 296–310. ISI Impact Factor (2015):  2.981
• Abirami, T., & Priakanth, P. (2014). Energy Efficient Wireless Sensor Network using Genetic Algorithm based Association Rules. International Journal of Computer Applications, 91(10).
• Ban, T. (2013). FUZZY COMPUTING FOR COMPLEXITY LEVEL OF EVALUATION TESTS. Studia Universitatis Babes–Bolyai, Informatica, 58(1).
• Mayadevi, N., Ushakumari, S. S., & Vinodchandra, S. S. (2014). SCADA–based operator support system for power plant equipment fault forecasting. Journal of The Institution of Engineers (India): Series B, 95(4), 369–376.
• Chen, H., Lonardi, S., & Zheng, J. (2014). Deciphering histone code of transcriptional regulation in malaria parasites by large–scale data mining. Computational biology and chemistry (Elsevier), 50, 3–10. ISI Impact Factor (2015): 1.014
• Banaee, H., & Loutfi, A. (2015). Data–Driven Rule Mining and Representation of Temporal Patterns in Physiological Sensor Data. IEEE Journal of Biomedical and Health Informatics, 19(5), 1557–1566. ISI Impact Factor (2015): 2.093
• Zeng, L., Wang, B., Fan, L., & Wu, J. (2016). Analyzing sustainability of Chinese mining cities using an association rule mining approach. Resources Policy, 49, 394–404. ISI Impact Factor (2015): 2.489
• Heraguemi, K. E., Kamel, N., & Drias, H. (2015). Association rule mining based on bat algorithm. Journal of Computational and Theoretical Nanoscience, 12(7), 1195–1200. ISI Impact Factor (2015): 1.665
• Kiran, G. A., Puri, M., & Suresh, S. S. (2017). PSO–Enabled Privacy Preservation of Data Clustering. Indian Journal of Science and Technology, 10(11).
• Dubey, Y., Singh, D., & Singh, A. (2016). A Parallel Early Binding Recursive Ant Colony Optimization (PEB–RAC) Approach for Generating Optimized Auto Test Cases from programming Inputs. International Journal of Computer Applications, 136(3), 11–17.
• Serkan Altuntas and Hasan Selim (2012) Facility layout using weighted association rule–based data mining algorithms: Evaluation with simulation. Expert Systems with Applications (Elsevier), 39(1), 2–13. IF(2015):  2.981
• Chidansh Amitkumar Bhatt and Mohan S. Kankanhalli (2011) Multimedia data mining: state of the art and challenges. Multimedia Tools and Applications (Springer), 51(1), 35–76. ISI Impact Factor (2015): 1.331
• Ting S.L., Wang W.M., Kwok S.K., Tsang Al. and Lee W.B. (2010) RACER: Rule–Associated CasE–based Reasoning for supporting General Practitioners in prescription making. Expert Systems with Applications (Elsevier), 37(12), 8079–8089. ISI Impact Factor (2015):  2.981
• Andrew Gelman, Iwin Leenen, Iven Van Mechelen, Paul De Boeck, Jeroen Poblone (2010) Bridges between deterministic and probabilistic models for binary data. Statistical Methodology (Elsevier), 7(3), 187–209. IF(2015): 0.74
• A.M.J. Md. Zubair Rahman, P. Balasubramanie (2009) Weighted Support Association Rule Mining using Closed Itemset Lattices in Parallel. International Journal of Computer Science and Network Security, 9(3): 247–253.
• Boris Gourévitch and Jos J. Eggermont (2010) Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise. Journal of Computational Neuroscience, 29(1–2):253–277. IF(2015): 1.871
• Basel A. Mahafzah, Amer F. Al–Badarneh, Mohammed Z. Zakaria (2009) A new sampling technique for association rule mining. Journal of Information Science (SAGE Publications), 35(3), 358–376. IF (2015): 0.878
• Tihomir Trifonov and Tsvetanka Georgieva (2009) Application for Discovering the Constraint–Based Association Rules in an Archive for Unique Bulgarian Bells. European Journal of Scientific Research, 31(3): 366–371, Impact Factor (2015): 0.736
• Basu C., Cheng H. and Butler D. (2008) Mining Spatial Associations with Limited Sensory Information. Spatial Cognition & Computation (Taylor & Francis), 8(1): 65–85. Impact Factor (2015): 0.760
• K.Ganeshkumar et al. (2012) “An Encrypted Technique with Association Rule Mining in Cloud Environment”. National Conference on Advancement of Technologies – Information Systems & Computer Networks (ISCON – 2012) Proceedings published in International Journal of Computer Applications® (IJCA), pp.5–8.
• Huang, Zifang, "Knowledge–Assisted Sequential Pattern Analysis: An Application in Labor Contraction Prediction" (2012). Open Access Dissertations. Paper 757. https://scholarlyrepository.miami.edu/oa_dissertations/757

• Ravindra Gupta, Prateek Gupta (2012) “Application Oriented Web Usage Mining with Customized Web Log Preprocessing & Frequent Pattern Tree”, International Journal of Engineering Research and Applications, Vol. 2, Issue 1, Jan–Feb 2012, pp.596–598
• K. Vanitha and R. Santhi (2011) USING HASH BASED APRIORI ALGORITHM TO REDUCE THE CANDIDATE 2– ITEMSETS FOR MINING ASSOCIATION RULE. Journal of Global Research in Computer Science. Volume 2, No. 5, April 2011.
• S.R. Mulik, S.G. Gulawani (2011) PERFORMANCE COMPARISON OF DATA MINING TOOLS IN MINING ASSOCIATION RULES. International Journal of Research in IT, Management and Engineering, Vol. 1, No. 3, pp. 330–336.
• Shanta Rangaswamy and Shobha G (2011) “ONLINE INDEXING FOR DATABASES USING QUERY WORKLOADS”. Vol. 2, No. 2, July–December 2011, pp. 427–433.
• BHAGIRATHI NAYAK, C. NAHAK & ARUN KR. MISRA (2011) FORCASTING OF FINANCIAL MARKETS – APPLICATION OF FUZZY ASSOCIATION RULES. International Journal of Research in Commerce, IT and Management, 1(5), 1–8.
• Rawat, S.S.; Rajamani, L. (2009) Performance of distributed apriori algorithms on a computational grid. 2009 IEEE Asia–Pacific Services Computing Conference (APSCC 2009), pp. 163 – 167. 7–11 Dec. 2009, Singapore.
• Rakhi Garg, P. K. Mishra (2011) Exploiting Parallelism in Association Rule Mining Algorithms, International Journal of Advancements in Technology, Vol. 2, No 2, pp. 222–232.
• Venkateswari S. and Suresh R.M (2011) ASSOCIATION RULE MINING IN ECOMMERCE: A SURVEY. International Journal of Engineering Science and Technology (IJEST), Vol. 3 No. 4, pp. 3086–3089.
•  Veenu Mangat (2010) Swarm Intelligence Based Technique for Rule Mining in the Medical Domain. International Journal of Computer Applications 4(1): 19–24, Published By Foundation of Computer Science.
• Kanhaiya Lal and N.C. Mahanti. (2010) Mining Association Rules in Large Database by Implementing Pipelining Technique in Partition Algorithm. International Journal of Computer Applications 2(4):33–39, June 2010. Published By Foundation of Computer Science.
• Rakhi Garg and Mishra (2010) Parallel Association Rule Mining Heterogeneous P K } = System. International Journal of Computer Applications 1(14): 81–85, February 2010. Published By Foundation of Computer Science.
• Tim Schluter and Stefan Conrad (2010) TARGEN: A market basket dataset generator for temporal association rule mining. Proceedings of the IADIS European Conference Data Mining 2009, pp.133–138.
• K. Rajendra Prasad, B. Bhaskara Rao, M. Surya Bhupal Rao and S.C.V. Ramana Rao (2010) An efficient analytical results from large databases. Proceedings of the Int. Conf. on Information Science and Applications ICISA, 6 February 2010, Chennai, India, pp.301–304
• B. Santhosh Kumar and K.V. Rukmani (2010) Implementation of Web Usage Mining Using APRIORI and FP Growth Algorithms. Int. J. of Advanced Networking and Applications, Vol. 1, No. 6, pp.400–404.
• V. Umarani and M.Punithavalli (2010). On Developing an Effectual Progressive Sampling–Based Approach for Association Rule Discovery. IEEE IMECS 2010 (ICIME), 2010 The 2nd IEEE International Conference on Information Management and Engineering, vol., no., pp.8–12, 16–18 April 2010.
• Veenu Mangat (2010) Swarm intelligence based technique for rule mining in the medical domain. International Journal of Computer Applications (0975–8887), Vol. 4, No. 1, pp.19–24, July 2010. Doi 10.5120/796–1131
• Olanrewaju Jelili Oyelade, Oladipupo, Olufunke Oyejoke (2010) Knowledge discovery from students’ result repository: Association Rule mining approach. International Journal of Computer Science & security (IJCSS), Vol. 4, No. 2, pp.199–207.
• Cristobal Romero, Jose Raul Romero, Jose Maria Luna and Sebastián Ventura (2010) “Mining rare association rules from e–learning data”.  EDM2010 The Third International Conference on Educational Data Mining. Pittsburgh, PA, USA June 11–13, 2010, pp.171–180.
• Kanhaiya Lal and N.C. Mahanti, (2010) “Mining association rules in large database by implementing pipelining technique in partition algorithm”, International Journal of Computer Applications, Vol. 2, No. 4, pp.33– 33–39, June 2010.
• S.A. Sahaaya Arul Mary and M. Malarvizhi (2010) “Improving Web Navigation Technique using Weighted Order Representation”. International Journal of Research and Reviews in Computer Science (IJRRCS), Vol. 1, No. 2, pp.55–60, June 2010.
• Nichnan Kittiphattanabawon, Thanaruk Theeramunkong and Ekawit Nantajeewarawat (2010) “Exploration of Document Relation Quality with Consideration of Term Representation Basis, Term Weighting and Association Measure”. Intelligence and Security Informatics, LNCS, Vol. 6122/2010, pp.126–139.
• Tianyi Wu (2010) “A framework for promotion analysis in multi–dimensional space”, PhD Dissertation, University of Illinois.
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• Shuo Wang, Ke Tang, Xin Yao, (2009) “Diversity exploration and negative correlation learning on imbalanced data sets,” IJCNN, pp.3259–3266, 2009 International Joint Conference on Neural Networks, 2009.
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• Yongmei Liu and Yong Guan (2009). Application in Market Basket Research on FP–Growth Algorithm. 2009 WRI World Congress on Computer Science and Information Engineering, Vol. 4, pp.112–115, March 31–April 2 2009.
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• M. Karagiannopoulos, D. Anyfantis, S. Kotsiantis and P. Pintelas, (2007). A Wrapper for Reweighting Training Instances for Handling Imbalanced Data Sets. IFIP Artificial Intelligence and Innovations 2007: from Theory to Applications, Vol.247/2007, pp.29–36.
• D. Anyfantis, M. Karagiannopoulos, S. Kotsiantis and P. Pintelas, (2007). Robustness of learning techniques in handling class noise in imbalanced datasets. IFIP Artificial Intelligence and Innovations 2007: from Theory to Applications, Vol. 247/2007, pp.21–28.
• Haidar, A. A. (2011). An adaptive document classifier inspired by t–cell cross–regulation in the immune system (Doctoral dissertation, Indiana University).

Kanellopoulos D., Kotsiantis S. and Pintelas P. (2006) Intelligent knowledge management for the travel domain. GESTS International Transactions on Computer Science and Engineering, 30(1), 95-106, April 30, 2006. ISSN: 1738-6438.

• Fernandes, J., Silva, A. D., & Albuquerque, E. (2017). The role of destination marketing organisation in strategic marketing management for tourism. GRA's Multidisciplinary International (GRAM i) Journal, 1, 8–22.
• El–Sofany, H., & Abou El–Seoud, S. (2011). Mobile Tourist Guide – An Intelligent Wireless System to Improve Tourism, using Semantic Web. International Journal of Interactive Mobile Technologies (iJIM), 5(4), 4–10.
• Ruiz–Martínez, J. M., Castellanos–Nieves, D., Valencia–García, R., Fernández–Breis, J. T., García–Sánchez, F., Vivancos–Vicente, P. J., ... & Martínez–Béjar, R. (2008, December). Accessing touristic knowledge bases through a natural language interface. In Pacific Rim Knowledge Acquisition Workshop (pp. 147–160). Springer, Berlin, Heidelberg.
• Almeida, C., Ferreira, A. M., & Costa, C. (2012). Aplicação de um modelo conceptual para o estudo de um novo produto turístico estratégico. O caso do Turismo residencial. III CONGRESSO INTERNACIONAL DE TURISMO DE LEIRIA E OESTE – 2009, Instituto Politécnico de Leiria. Available at: https://cassiopeia.esel.ipleiria.pt/esel_eventos/files/3903_13_ClaudiaAlmeida_4bf565ee68bfa.pdf
• Damljanovic D., Devedzic V. (2009) “Semantic Web and e–tourism”. In Mehdi Khosrow–Pour (Ed.) Encyclopedia of Information Science and Technology, Vol. VII, 2^nd Ed., IGI Global, Hershey, PA, 2009, pp.3426–3432.
• Waralak V. Siricharoen (2007) “Ontologies for E–tourism”, 4th WSEAS/IASME International Conference on ENGINEERING EDUCATION (EE'07).

Kanellopoulos D. (2006) Modifications of the IEEE LTSA reference model for new e-learning environments. Open Education: The journal for Open and Distance Education and Education Technology, 2(4), 75-95. ISSN: 1790-3254-4.

• Lazarinis F., Green S. and Pearson E. (2008) Measuring the conformance of hypermedia assessment tools to QTI. International Journal of Innovation and Learning (Inderscience), 6(2), 127-146.

Kanellopoulos D. and Panagopoulos A. (2008) Exploiting tourism destinations’ knowledge in a RDF-based P2P network. Journal of Network and Computer Applications (Elsevier), 31(2), 179-200. ISI 5-Year Impact Factor: 2.485

• Liu, M., Koskela, T., Ou, Z., Zhou, J., Riekki, J., & Ylianttila, M. (2011). Super-peer-based coordinated service provision. Journal of Network and Computer Applications, 34(4), 1210-1224. ISI 5-Year Impact Factor: 2.485
• Chen, Y. H., Lu, E. J. L., Chang, Y. T., & Huang, S. Y. (2016). RDF-Chord: A hybrid PDMS for P2P systems. Computer Standards & Interfaces (Elsevier), 43, 53-67. Impact Factor (2015): 1.268
• Pereira, R. L., Sousa, P. C., Barata, R., Oliveira, A., & Monsieur, G. (2015). CitySDK Tourism API-building value around open data. Journal of Internet Services and Applications (Springer), 6(1), 24.
• Ruiz-Martınez, J. M., Minarro-Giménez, J. A., Castellanos-Nieves, D., Garcıa-Sánchez, F., & Valencia-Garcia, R. (2011). Ontology population: an application for the e-tourism domain. International Journal of Innovative Computing, Information and Control (IJICIC), 7(11), 6115-6134.
• Tseng, H. C., Tu, P. P. N., Lee, Y. C., & Wang, T. S. (2012). A study of user acceptance of destination management systems in Taiwan tourism with the modified technology acceptance model. Journal of Convergence Information Technology, 7(10).
• Siricharoen, W. V. (2010). Enhancing semantic web and ontologies for e-tourism. International Journal of Intelligent Information and Database Systems, 4(4), 355-372.
• Ángel García-Crespo et al. (2010) “Intelligent Decision-Support Systems for e-Tourism: Using SPETA II as a Knowledge Management Platform for DMOs and e-Tourism Service Providers”. International Journal of Decision Support System Technology (IJDSST) Vol. 2, No.1, pp.36-48.
• García-Crespo, Á., Colomo-Palacios, R., Gómez-Berbís, J. M., Chamizo, J., & Rivera, I. (2012). Intelligent Decision-Support Systems for e-Tourism: Using SPETA II as. Integrated and Strategic Advancements in Decision Making Support Systems, 37.
• García-Barriocanal, E., & Sicilia, M. A. (2008). On linking cultural spaces and e-tourism: An ontology-based approach. The Open Knowlege Society. A Computer Science and Information Systems Manifesto, 694-701.
• Nina Mistilis, Dimitrios Buhalis (2012) Challenges and potential of the Semantic Web for tourism. e-Review of Tourism Research (eRTR), Vol. 10, No. 2, 2012, https://ertr.tamu.edu. Special Issue – ENTER 2012 Idea Exchange.
• Bauer, L., Boksberger, P., Herget, J., Hierl, S., & Orsolini, N. (2008). The virtual dimension in tourism: Criteria catalogue for the assessment of eTourism applications. Information and Communication Technologies in Tourism 2008, 521-532.
• Wenyun, L., & Lingyun, B. (2009, December). Application and exploration of travel-service and information system based on web service. In Computational Intelligence and DeSign, 2009. ISCiD'09. Second International Symposium on (Vol. 1, pp. 438-441). IEEE.
• Colomo-Palacios, R. (2013). Semantic Technologies in Motion: From Factories Control to Customer Relationship Management. In Industrial Engineering: Concepts, Methodologies, Tools, and Applications (pp. 477-498). IGI Global.
• MAICAN, C., & Lixăndroiu, R. (2014). A PROPOSAL FOR AN INTERACTIVE SYSTEM FOR ASSISTING TOURIST DECISION MAKING. Management & Marketing, 9(2).
• Chatzitoulousis, A., Efraimidis, P. S., & Athanasiadis, I. N. (2015, September). Interoperable Multimedia Annotation and Retrieval for the Tourism Sector. In Research Conference on Metadata and Semantics Research (pp. 65-76). Springer International Publishing.
• Maria Teresa Linaza, Cristina Sarasua, Yolanda Cobos (2009) MPEG-7 Compliant Indexation Tool for Multimedia Tourist Content. Information and Communication Technologies in Tourism 2009 (pp. 249-260) Editors: Wolfram Höpken, Ulrike Gretzel and Rob Law. Publisher: Springer Vienna. Doi: 10.1007/978-3-211-93971-0_21
• Tria, S. B., Seridi-Bouchelaghem, H., & Mokhati, F. (2016). An Ontology-Based Context Model to Manage Users Preferences And Conflicts. Informatica, 40(1), 71.
• Shi, M., Zhu, W., Yang, H., & Li, C. (2016). Applying semantic web and big data techniques to construct a balance model referring to stakeholders of tourism intangible cultural heritage. International Journal of Computer Applications in Technology (Inderscience), 54(3), 192-200.
• Liu Wenyun, Bao Lingyun (2009) Application and Exploration of Travel-Service and Information System Based on Web Service. 2009 Second International Symposium on Computational Intelligence and Design (ISCID), Vol. 1, pp.438-441.
• Mudiyanselage, R. D. (2014). Ontology-based Search Algorithms over Large-Scale Unstructured Peer-to-Peer Networks (Doctoral dissertation, ScholarWorks@ Georgia State University).

[J9] Kanellopoulos D. (2006) The advent of semantic web in tourism information systems”, Tourismos: An International Multidisciplinary Journal of Tourism, 1(2): 75-91, ISSN: 1790-8418.

• Munar, A. M., Gyimóthy, S., & Cai, L. (Eds.). (2013). Tourism social media: Transformations in identity, community and culture. Emerald Group Publishing.
• Ek, R. (2013). Tourism social media as a fire object. In Tourism Social Media: Transformations in Identity, Community and Culture (pp. 19-34). Emerald Group Publishing Limited.
• Chainas, K. (2012). The Optimization Of The Greek Coastal Shipping Transportation Network. Tourismos: An International Multidisciplinary Journal Of Tourism, 7(1), 351-366.
• M. Thangaraj, R. Somasundara Manikanda (2011) “A survey on semantic web based e-Tourism dynamic package”, International Journal of Computer Science and Information Technologies, 2(2), 611-613.
• Dibyendra Hyoju (2010) “Semantic tourism information system”. Dissertation. Department of Computer Science & Engineering. Kathmandu University. Oct. 2010. Available at: https://www.docstoc.com/docs/71733889/Semantic-Tourist-Information-System.
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• Danica Damljanovic (2007) Intelligent Web portal in the area of Tourism. Department of Information Systems, University of Belgrade, Serbia. (MSc Information Systems- Supervisor: Prof. Vladan Devedzic).

[J8] Kotsiantis S., Kanellopoulos D. and Pintelas P. (2006) Data preprocessing for supervised learning. International Journal of Computer Science, 1(2): 111-117.

• Zhang Y et al. (2018) FingerAuth: 3D magnetic finger motion pattern based implicit authentication for mobile devices. Future Generation Computer Systems. ISI Impact Factor (2016): 3.997
• Chen, Z. G., Kang, H. S., Yin, S. N., & Kim, S. R. (2017, September). Automatic Ransomware Detection and Analysis Based on Dynamic API Calls Flow Graph. In Proceedings of the International Conference on Research in Adaptive and Convergent Systems (pp. 196-201). ACM.
• Lu, T., Sun, J., Wu, K., & Yang, Z. (2018). High-Speed Channel Modeling With Machine Learning Methods for Signal Integrity Analysis. IEEE Transactions on Electromagnetic Compatibility. ISI Impact Factor (2016): 1.658
• Kern, A. N., Addison, P., Oommen, T., Salazar, S. E., & Coffman, R. A. (2017). Machine learning based predictive modeling of debris flow probability following wildfire in the intermountain Western United States. Mathematical Geosciences, 49(6), 717-735. ISI Impact Factor (2016): 2.022
• Okamura, R., Iwabuchi, H., & Schmidt, K. S. (2017). Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning. Atmospheric Measurement Techniques, 10(12), 4747-4759. ISI Impact Factor (2016): 3.089
• Despoina Chatzakou, Athena Vakali, Konstantinos Kafetsios, Detecting Variation of Emotions in Online Activities, Expert Systems With Applications (2017), doi: 10.1016/j.eswa.2017.07.044 ISI Impact Factor (2015): 2.981
• H. Oh; S. Ahn; J. Kim; S. Lee, "Blind Deep S3D Image Quality Evaluation via Local to Global Feature Aggregation," in IEEE Transactions on Image Processing, vol.PP, no.99, pp.1-1 doi: 10.1109/TIP.2017.2725584 Impact Factor (2015): 4.828
• W.K. Wong, Z.X. Guo  (2010) A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm. International Journal of Production Economics (Elsevier), 128(2), 614-624. Impact Factor (2015): 2.782
• Jha, S.K.; Yadava, R.D.S. (Oct. 2009) Preprocessing of SAW Sensor Array Data and Pattern Recognition. IEEE Sensors Journal, 9(10), 1202-1208. Impact Factor (2015): 1.889
• Isler Y. and Kuntalp M. (2010) Heart rate normalization in the analysis of heart rate variability in congestive heart failure. Proceedings of the Institution of Mechanical Engineers, Part H. Journal of Engineering in Medicine (SAGE) 224(3), 453-463. Impact Factor (2015): 0.996
• Zuriani Mustaffa, Yuhanis Yusof (2011) “Optimizing LSSVM Using ABC for Non-Volatile Financial Prediction”. Australian Journal of Basic and Applied Sciences, 5(11): 549-556, 2011
• Khalid Abu Al-Saud, Massudi Mahmuddin and Amr Mohamed (2012) “Wireless Body Area Sensor Networks Signal Processing and Communication Framework: Survey on Sensing, Communication Technologies, Delivery and Feedback”, Journal of Computer Science, 8 (1): 121-132, 2012, ISSN 1549-3636.
• Mazni Omar, Sharifah-Lailee Syed-Abdullah and Naimah Mohd Hussin (2011) “Developing a team performance prediction model: A Rough Sets Approach”. Communications in Computer and Information Science, 2011, Volume 252, Part 5, 691-705, DOI: 10.1007/978-3-642-25453-6_58
• Khalid Abu Al-Saud, Massudi Mahmuddin and Amr Mohamed (2012) “Wireless Body Area Sensor Networks Signal Processing and Communication Framework: Survey on Sensing, Communication Technologies, Delivery and Feedback”. Journal of Computer Science 8(1): 121-132, 2012.
• Al Jarullah, A.A (2011) “Decision tree discovery for the diagnosis of type II diabetes”, 2011 IEEE International Conference on Innovations in Information Technology (IIT), pp.303-307.
• B. Byeon and K. Rasheed (2010) “Bayesian Networks and Genetic Algorithms for Promoter Recognition”, Proceeding (705) IASTED Technology Conferences - 2010
• J. Prabhu, M. Sudharshan, M. Saravanan, G. Prasad (2010) "Augmenting Rapid Clustering Method for Social Network Analysis," asonam, pp.407-408, 2010 International Conference on Advances in Social Networks Analysis and Mining, 2010.
• Jan Hummel, Nadine Strehmel, Joachim Selbig, Dirk Walter, Joachim Kopka (2010) “Decision tree supported substructure prediction of metabolites from GC-MS profiles”. Metalobomics (Springer), Vol. 6, No. 2, pp. 322-333. doi: 10.1007/s11306-010-0198-7.
• Jan Carlos Barca (2009) “New Multicolour Illuminated Contour-based Markers and their use in Motion Capture”, PhD Thesis, Monash University. Australia.
• Mikael Kuusela, Jerry W. Lämsä, Eric Malmi, Petteri Mehtälä and Risto Orava  (2009) “Multivariate Techniques for Identifying Diffractive Interactions at the LHC”. [Online:] https://arxiv.org/ftp/arxiv/papers/0909/0909.3039.pdf
• Boseon Byeon and Khaled Rasheed (2008) “Simultaneously Removing Noise and Selecting Relevant Features for High Dimensional Noisy Data”. 2008 Seventh IEEE International Conference on Machine Learning and Applications. pp.147-152.
• Christopher Hogan, Dan Brassil, Shana M. Rugani, Jennifer Reinhart, Misti Gerber and Teresa Jade (2008) “H5 at TREC 2008 Legal Interactive: User Modeling, Assessment & Measurement”. In Proc. of the Seventeenth Text REtrieval Conference, TREC 2008, Gaithersburg, Maryland, USA, November 18-21. Editors: Ellen M. Voorhees and Lori P. Buckland. Publisher: National Institute of Standards and Technology (NIST). Vol. special publication 500-277. 
• Isler Y. and Kuntalp M. (2007) “Combining Classical HRV Indices With Wavelet Entropy Measures Improves to Performance in Diagnosing Congestive Heart Failure”, Computers in Biology and Medicine (Elsevier Science), Vol. 37, No. 10, pp.1502-1510.
• Hickman J., Hope G., Wang T. (2007) “Data attribute Selection using genetic programming”. International Conference on Information Society (i-Society 2007), pp.357-364.
• Kriger C. and Tzoneva R. (2007) “Neural networks for prediction of wastewater treatment plant influent disturbances”, AFRICON 2007, 26-28 Oct. 2007, pp.1-7.

Kotsiantis S., Kanellopoulos D. and Tampakas V. (2006) On implementing a financial decision support system. International Journal of Computer Science and Network Security, 6(1A): 103-112. [Emerging Sources Citation Index]

• García, V., Marqués, A. I., & Sánchez, J. S. (2012). On the use of data filtering techniques for credit risk prediction with instance-based models. Expert Systems with Applications, 39(18): 13267-13276. ISI Impact Factor (2015): 2.981
• Pai, D. R., Lawrence, K. D., Klimberg, R. K., & Lawrence, S. M. (2012) Experimental comparison of parametric, non-parametric, and hybrid multigroup classification. Expert Systems with Applications, 39(10): 8593-8603. ISI Impact Factor (2015): 2.981
• Kirkos E., Spathis C. and Manolopoulos Y. (2008) Support vector machines, Decision Trees and Neural networks for auditor selectio. Journal of Computational Methods in Sciences and Engineering (IOS Press), 8(3): 213-224. [Emerging Sources Citation Index]
• Badgujar, H., & Thool, R. C. (2013). INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET). Journal Impact Factor, 4(2), 198-212.
• Antonio Wong, Pak-Lok Poon (2009) “Using Information Technologies to Restore Investor Trust”, ISACA Journal, Vol. 5, pp.1-5.

Kanellopoulos D., Kotsiantis S. and Pintelas P. (2006) ‘Considering the educational semantic Web’, Themes in Education, 7(2), 145-164.

• Cheniti-Belcadhi L., Henze N. and Braham R. (2008) Assessment personalization in the Semantic Web. Journal of Computational Methods in Sciences and Engineering (IOS Press), 8(3), 163-182. [Emerging Sources Citation Index]
• Stavrinoudis D. and Xenos M. (2008) On technological issues affecting online learners' behaviour. Journal of Computational Methods in Sciences and Engineering (IOS Press), 8(3), 183-194. [Emerging Sources Citation Index]

Sakkopoulos E., Kanellopoulos D. and Tsakalidis A. (2006) Semantic mining and web service discovery techniques for media resources management. International Journal of Metadata, Semantics and Ontologies (Inderscience Publishers), 1(1), 66-75.

• Plegas Y., Sakkopoulos E. and Tsakalidis A. (2007) “Augmenting semantic queries using personalization techniques”, 11th Panhellenic Conference in Informatics, pp. 491-504.
• Zhang, Q., & Segall, R. S. (2008). Web mining: a survey of current research, techniques, and software. International Journal of Information Technology & Decision Making, 7(04), 683-720.
• Makripoulias Y., Makris C., Panagis Y., Sakkopoulos E., Adamopoulou P. and Tsakalidis A. (2006) Web Service discovery based on Quality of Service. IEEE International Conference on Computer Systems and Applications, pp.196-199, March 8, 2006.
• Makripoulias, Y., Makris, C., Panagis, Y., Sakkopoulos, E., Adamopoulou, P., Pontikaki, M., & Tsakalidis, A. (2005). Towards ubiquitous computing with quality of web service support. Upgrade, The European Journal for the Informatics Professional VI (5), 29-34.
• Antoniou, D., Paschou, M., Sourla, E., & Tsakalidis, A. (2010, September). A Semantic Web Personalizing Technique: The Case of Bursts in Web Visits. In Semantic Computing (ICSC), 2010 IEEE Fourth International Conference on (pp. 530-535). IEEE.
• Adamopoulou, P., Sakkopoulos, E., Tsakalidis, A. K., & Lytras, M. D. (2007). Web Service Selection based on QoS Knowledge Management. J. UCS, 13(9), 1138-1156.
• Sakkopoulos, E. (2009). Semantic technologies for mobile Web and personalized ranking of mobile Web search results. In Metadata and Semantics (pp. 299-308). Springer US.
• Zhuhua Liao, Jing Yang, Chuan Fu and Guoqing Zhang (2011) CLUENET: Enabling automatic video aggregation in social media networks. K.-T. Lee et al. (Eds.)  Advances in Multimedia Modeling. (Springer) Lecture Notes in Computer Science, 2011, Volume 6524/2011, pp.274-284.
• E. Sakkopoulos, C. Costopoulou, M. Ntaliani, A. Liopa-Tsakalidis, A. Sideridis (2011) An Architecture of m-Learning Environment for Medicinal and Aromatic Plants. Journal of Information Technology in Agriculture, Vol. 4, No.1.
• Greer K., Baumgarten M., Mulvenna M., Nugent C. and Curran K. (2009) An infrastructure for developing self-organising services. International Journal of Adaptive and Innovative Systems (Inderscience Publishers), 1(1), 88-103.
• Qingyu Zhang and Richard S. Segall (2008) Web Mining: A survey of current research, techniques, and software. International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd, Vol. 7, No. 4, pp.683-720.
• Plegas Y., Sakkopoulos E. and Tsakalidis A. (2007) Augmenting semantic queries using personalization techniques. 11th Panhellenic Conference in Informatics, pp.491-504.
• Danica Damljanovic (2007) Intelligent Web portal in the area of Tourism. Department of Information Systems, University of Belgrade, Serbia. (MSc on Information Systems- Supervisor: Prof. Vladan Devedzic).
• Makris C. (2006) IT Application Development with Web Services. In Encyclopedia of Information Science & Technology, 2nd edition (Ed. Medhi Khosrow-Pour). IDEA Group Inc., pp.2278-2284

Kanellopoulos D., Panagopoulos A. and Psillakis Z. (2004) Multimedia applications in Tourism: The case of travel plans. Tourism Today, No. 4, pp.146-156.

• Ferraro, P., & Re, G. L. (2014). Designing Ontology-Driven Recommender Systems for Tourism. In Advances onto the Internet of Things (pp. 339-352). Springer International Publishing.
• Kenneth Cosh (2010) The introduction of ICT’s into the Tourism industry: A detailed study with focus on Thailand. Computer Information Systems, Payap University. Available at: https://cis.payap.ac.th/wp-content/uploads/2010/06/The-Introduction-of-ICTs-into-the-Tourism-Intustry-Dr.-Ken-Cosh.pdf
• Lazarinis F. (2006) Evaluating the technologies and services of tourism and cultural web sites. International Conference of Trends, Impacts and Policies on Tourism Development, Heraklion, Crete, Greece. 15-18 June 2006.

Kotsiantis S., Kanellopoulos D. and Pintelas P. (2004) Multimedia mining. WSEAS Transactions on Systems, 3(10): 3263-3268.

• Manjunath T.N., Ravindra S. Hegadi, Ravikumar G.K. (2010) A survey on multimedia data mining and its relevance today. International Journal of Computer Science and Network Security, 10(11), 165-170.
• Kumar, D., & Bhardwaj, D. (2011). Rise of data mining: Current and future application areas. IJCSI International Journal of Computer Science Issues, 8(5).
• Venkatadri, M., & Reddy, L. C. (2011). A review on data mining from past to the future. International Journal of Computer Applications, 15(7), 19-22.
• Vijayakumar, V., & Nedunchezhian, R. (2012). A study on video data mining. International journal of multimedia information retrieval, 1(3), 153-172.
• Paidi, A. N. (2012). Data mining: Future trends and applications. International Journal of Modern Engineering Research (IJMER), 2(6), 4657-4663.
• Goele, S., & Chanana, N. (2012). Data Mining Trend In Past, Current And Future. International Journal of Computing & Business Research.
• Manickam, R., Boominath, D., & Bhuvaneswari, V. (2012). An analysis of data mining: past, present and future. International journal of Computer Engineering and Technology (IJCET), 3(1), 1-9.
• Vijayarani, S., & Sakila, A. (2015). Multimedia Mining Research-An Overview. International Journal of Computer Graphics & Animation, 5(1), 69.
• More, S., & Mishra, D. K. (2012). Multimedia Data Mining: A Survey. Pratibha: International Journal of science, spirituality, business and technology (ijssbt), 1(1).
• Reddy, L. C. (2011). A Review on Data mining from Past to the Future. International Journal of Computer Applications, 7(4), 19-22.
• Guleria, P., & Sood, M. (2014). Data Mining In Education: A review on The Knowledge Discovery Perspective. International Journal of Data Mining & Knowledge Management Process, 4(5), 47.
• Akeem, O. A., Ogunyinka, T. K., & Abimbola, B. L. (2012). A framework for multimedia data mining in information technology environment. International Journal of Computer Science and Information Security, 10(5), 69.
• Singh, L. (2013). Data Mining: Review, Drifts and Issues. International Journal of Advance Research and Innovation, 2, 44-48.
• Vijayakumar, V., & Nedunchezhian, R. (2011). Mining Best-N Frequent Patterns in a Video Sequence. International Journal on Computer Science and Engineering, 3(11), 3525.
• Ravikumar, G. K., Manjunath, T. N., Hegadi, R. S., & Archana, R. A. (2011). A STUDY ON DESIGN AND ANALYSIS OF WEB MART MINING AND ITS RELEVANCE TODAY. International Journal of Engineering Science and Technology, 1(3), 3141-3152.
• Hu, H., & Kantardzic, M. (2016, January). Smart Preprocessing Improves Data Stream Mining. In System Sciences (HICSS), 2016 49th Hawaii International Conference on (pp. 1749-1757). IEEE.
• Janice Kwan-Wai Leung (2009) Commentary-based video categorization and concept discovery. The 2nd Workshop on Social Web Search and Mining (SWSM) in conjunction with CIKM 2009. November 26, 2009, Hong Kong.
• FP6-027026, K-Space ID4.1: State-of-the-art Report on Knowledge Assisted Multimedia Analysis.
• FP6-027026, K-Space ID4.1.1: State-of-the-art Report on Multimedia Mining.

[C1]  Orphanos G., Kanellopoulos D., Kopsahili, E., Koubias S. and Papadopoulos G. (1992) “Extending OSI protocols to support Medical Imaging Services”, 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1284-1286, Paris, France, October 1992.

• Herron, J. M., Lattner, S., King, J. L., Gur, D., Oliver III, J. H., Plunkett, M. B., & Towers, J. D. (1993, September). Device and system performance expectations in clinical PACS. In Medical Imaging 1993 (pp. 58-62). International Society for Optics and Photonics.

[C2]  Orphanos G., Kanellopoulos D., Prentzas L., Koubias S. and Papadopoulos G. (1993) Proposed Teleworking Platform for Workstations Supporting Multimedia Medical Applications. PACS: Design and Evaluation, SPIE Medical Imaging '93, Vol. 1899, pp.72-83, Newport Beach, California USA, February 1993.

• D. Lymperopoulos et al. (1995) ELPIDA: a general architecture for medical imaging systems supporting telemedicine applications. Journal of Electronic Imaging, 4(1), 84-97, January 1995.
• D. Lymperopoulos et al. (1994) An homogeneous medical tele-working domain supported by a new remote expert consultation conferencing service. Journal of European Transactions on Telecommunications (Wiley), 5(4), 495-507, Jul. Aug. 1994. Impact Factor: 1.295

[C3] Orphanos G., Kanellopoulos D. and Koubias S. (1993) Communication Software for Physicians' Workstations Supporting Medical Imaging Services. PACS: Design and Evaluation, SPIE Medical Imaging '93, Vol. 1899, pp.476-485, Newport Beach, California USA, February 1993.

• Yoo S.K, Kim S.H., Kim N.H., Kang Y.T., Kim K.M., Bae S.H., Vannier M.W. (2001) Design of a PC-based multimedia telemedicine system for brain function teleconsultation. International Journal of Medical Informatics (Elsevier), 61(2-3), 217-227. Impact Factor: 2.363
• Yoo S.K, Kim K.M., Kim N.H., Huh J.M, Chang B.C., Cho B.K. (1997) Design of a medical image processing software for clinical-PACS. Yonsei Medical Journal, 38(4), 193-201. Impact Factor: 1.234

[C4] Orphanos G., Kanellopoulos D., Koubias S. and Papadopoulos G. (1994) An integrated application/service platform to support multimedia applications. IEEE SUPERCOMM/ICC '94, pp.1722-1726, New Orleans, Louisiana, USA, May 1994.

• Israel Cidon, Shay Kutten, and Ran Soffer (2002) Optimal allocation of electronic content. Computer Networks (Elsevier), 40(2), 205-218. Impact Factor: 1.446
• D. Lymperopoulos et al. (1994) An homogeneous medical tele-working domain supported by a new remote expert consultation conferencing service. Journal of European Transactions on Telecommunications (Wiley), 5(4), 495-507, Jul. Aug. 1994. Impact Factor: 1.295
• D. Lymperopoulos et al. (1995) ELPIDA: a general architecture for medical imaging systems supporting telemedicine applications. Journal of Electronic Imaging (SPIE), 4(1), 84-97, January 1995.
• Israel Cidon, Shay Kutten and Ran Soffer (2001) Optimal allocation of electronic content. IEEE INFOCOM, April 22-26, 2001.
• Bu-Ihl Kim, Sun-Moo Kang, Hyuan-Sook Lee, and Young-So Cho (1997) Experimental considerations of the public ATM network to accommodate high-speed multimedia communication services. IEEE ATM Workshop 1997. Proceedings, 25-28 May 1997, pp. 320-326.
• Pandya Suketu J. and Lakshmanan, Hariharan (2003) Software, Systems and Methods for Managing a Distributed Network. No. 6671724 USA PATENT OFFICE, December 30, 2003, https://www.freepatentsonline.com/6671724.html
• Mizuguchi Yuji, Sakai Takahisa, Ikeda Toshihisa, Kurosaki Toshihiko, Moriguchi Kenichi, Oga Toshio (2001) Communication network. No 6320871 USA PATENT OFFICE, https://www.freepatentsonline.com/6320871.html

[C7] Kanellopoulos D. et al. (1995) Client-Server Computing Requirements of Networked Multimedia Services. IEE Computing and Control Division, International Seminar on Client/Server Computing, pp.3/1-3/15, IBM-La Hulpe, Belgium, 30-31 Oct. 1995.

• Hui, J.Y.  Karasan, E.  Li, J.  Zhang, J. (1996) Client-server synchronization and buffering for variable rate multimedia retrievals. IEEE Journal on Selected Areas in Communications, 14(1), 226-237. Impact Factor (2015):  3.672
• David G. Messerschmitt (August 1996) The convergence of telecommunications and computing: What are the implications today?. IEEE Proceeding, 84(8), 1167-1186. Impact Factor (2015): 5.629 

[C8] Kanellopoulos D., Papadopoulos G. and Koubias S. (1996) A novel ACSE protocol with comprehensive QoS support for multimedia communications in Chorus. In Proc. ICUPC ‘96 - 5th IEEE International Conference on Universal Personal Communications, pp.487-491, Cambridge, Massachusetts, USA, 29 Sept.- 2 Oct. 1996. ISBN: 07803-3300-4.

• OREN, Yair (2000) Virtual Star Network (Chromatics Networks, Inc). Patent record EP1058979 available from the European Patent Office [https://www.epoline.org/]

[C11] Kanellopoulos D., Koubias S. and Papadopoulos G. (1996) The comprehensive QoS approach and the evolution of ACSE protocols in multimedia communications. In Proc. of the 3^rd ΙΕΕΕ International Conference on Electronics, Circuits and Systems (ICECS’96), Vol. 1 (ISBN: 0-7803-3650-X), pp.323-326, Rodos, Greece, October 13-16, 1996.

• Jefferson Eugene O., Raul Zegers D. and Osvaldo C. (2008) Electronic system and method for display using a decoder and arbiter to selectively allow access to a shared memory. No 7331368 USA PATENT OFFICE, January 22, 2008. https://www.frepatentsonline.com/7321368.html
• Butler Laura J. (2007) Scalable multiparty conferencing and collaboration system and method of dynamically allocating system resources in same. No 7167182 USA PATENT OFFICE, https://www.freepatentsonline.com/7167182.html
• Butler Laura J. (2006) Scalable multiparty conferencing and collaboration system and method of dynamically allocating system in resources and providing true color support in same. No 7136062 USA PATENT OFFICE, https://www.freepatentsonline.com/7136062.html
• Liles Jane R., and Giloi Claus T. (2005) Multiparty conference authentication. No 6851053 USA PATENT OFFICE, February 1, 2005, https://www.freepatentsonline.com/6851053.html
• Giloi Claus T., MacLin, Markham F., and Morris Max G.               (2005)     Security and support for flexible conferencing topologies spanning proxies, firewalls and gateways. No 6850985 USA PATENT OFFICE, https://www.freepatentsonline.com/6850985.html
• Dubrow Deborah L., Butler Laura J., Dailey Jane L., and Giloi, Claus T. (2003) Application Sharing in a Frame. No 6570590 USA PATENT OFFICE, May 27, 2003, https://www.freepatentsonline.com/6570590.html
• Butler Laura J. (2003) Multiparty conferencing and collaboration system utilizing a per-host model command, control and communication structure. No 6584493 USA PATENT OFFICE, https://www.freepatentsonline.com/6584493.html
• Butler Laura J. (2000) Scalable multiparty conferencing and collaboration system and method of dynamically allocating system resources, Patent record available from the World Intellectual Property Organization (WIPO).

[C12]  Adamopoulou P., Kanellopoulos D., Sakkopoulos E. and Tsakalidis A. (2005) “Semantic learning interventions using Web Services technology”, IASTED 2005 International Conference on Web Based Education (WBE 2005), Web Based Teaching and Learning Technologies track, 2/2005, pp.528-533.

• Y. Makripoulias, Ch. Makris, E. Sakkopoulos, Y. Panagis, P. Adamopoulou and A. Tsakalidis (2005) Towards Ubiquitous Computing with Quality of Web Service support. Upgrade: The European Journal for the Informatics Professional, Vol. VI, No 5, pp. 29-34, Oct 2005.

[C15]  Kanellopoulos D. and Panagopoulos A. (2005) Exploiting tourism destinations’ knowledge in an RDF-based P2P network.  ACM Hypertext 2005. First International Workshop WS4–Peer to peer and Service Oriented Hypermedia: Techniques and Systems.

• Lydia Bauer, Philipp Boksberger, Josef Herget, Sonja Hierl and Noelene Orsolini (2008) “The Virtual Dimension in Tourism: Criteria Catalogue for the Assessment of eTourism Applications”, In Information and Communication Technologies in Tourism 2008 (Peter O’Connor, Wolfram Höpken and Ulrike Gretzel Eds.) pp. 521-532.

[C16] Kanellopoulos D., Kotsiantis S. and Pintelas P. (2006) Ontology-based learning applications: A development methodology. IASTED International Conference on Software Engineering (SE 2006), February 14-16, 2006, Innsbruck, Austria, (pp.27-32).

• Ouf, S., Ellatif, M. A., Salama, S. E., & Helmy, Y. (2016). A proposed paradigm for smart learning environment based on semantic web. Computers in Human Behavior. Impact Factor (2015): 2.880
• Ling, C. P., Noor, N. M. M., & Mohd, F. (2017). Knowledge Representation Model for Crime Analysis. Procedia Computer Science, 116, 484-491.
• Laksitowening, K. A., Yanuarifiani, A. P., & Wibowo, Y. F. A. (2016, October). Enhancing e-learning system to support learning style based personalization. In Science in Information Technology (ICSITech), 2016 2nd International Conference on (pp. 329-333). IEEE.
• Bodea, C. N., Dascalu, M., & Coman, M. (2010). Quality of project management education and training programmes. In Technology Enhanced Learning. Quality of Teaching and Educational Reform (pp. 324-330). Springer Berlin Heidelberg.
• B. Falcidieno, M. Pitakis, M. Spanguolo, M. Vavalis, C. Houstis (2010) “FOCUS K3D: Promoting the use of knowledge intensive 3D media”.
• Funda Dag, Kadir Erkan (2009) “Realizing the personalized learning paths in a LMS”. Paper presented at the International Educational Technology (IETC) Conference (7th, Nicosia, Turkish Republic of Northern Cyprus, May 3-5, 2007).
• Bodea, V., Sabau, G., & Sandu, D. (2007). E-Learning–A Solution for Project Management Excellence. Projektna mreža Slovenije, 35.
• Manolis Vavalis (2008) “On the impact of knowledge management of 3-Dimensional Archaeology & Cultural Heritance”. The 14th International Conference on Virtual Systems and MultiMedia VSMM 2008, Workshops on Digital Heritage. M. Ioannides, A. Addison, A. Georgopoulos and L. Kalisperis.
• Graudiņa Vita. (2007) An overview of ontology usage in computer-based tutoring systems. Annual Proceedings of Vidzeme University College. ICTE in Regional Development. - Valmiera, Latvia: Vidzeme University College, 2007. - pp 70-77.
• C.-N. Bodea (2007) “An Innovative System for Learning Services in Project Management”. IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI 2007), 27-29 August 2007, pp.1-5. 
• C.-N. Bodea (2007) “Ontology-based Learning in Project Management”, Proc. of the 6th Conference on E-learning: ECEL 2007, pp. 119-127.
• Antonella Carbonaro and Rodolfo Ferrini (2007) “Personalized information retrieval in a semantic-based learning environment”, Chapter XIV, pp. 270-287. In  “Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively”, Edited by Dion Goh and Schubert Foo. Publisher: Information Science Reference.
• Toshihiro Morioka, Noriyouki Iwane and Yukihiro Mathubara (2007) “A study on building of Japanese history ontology aiming at learning support”. In Frontiers in Artificial Intelligence and Applications, Vol. 162, pp.109-112. In Supporting Learning Flow through Integrative Technologies. T. Hirashima et al. (Eds) IOS Press. 2007.
• Bodea, C. N., Dascalu, M. I., & Lipai, A. (2011). Clustering of the web search results in educational recommender systems. Educational Recommender Systems and Technologies: Practices and Challenges: Practices and Challenges, 154.
• Yusof, N., Mansur, A. B. F., & Othman, M. S. (2011, September). Ontology of moodle e-learning system for social network analysis. In Open Systems (ICOS), 2011 IEEE Conference on (pp. 122-126). IEEE.
• Bodea, C. N. (2009) Project management competences development using an ontology-based e-learning platform. M.D. Lytras et al. (Eds.): WSKS 2009, LNAI 5736, pp.31-39, 2009. Springer-Verlag Berlin Heidelberg 2009.
• Bodea, C. N. (2012). Business Intelligence in Higher Education: An Ontological Approach. In Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications (pp. 285-312). IGI Global.
• Oprea, M. (2015, September). On the Design of a Collaborative Ontology Development Methodology for Educational Systems. In Proceedings of the 7th Balkan Conference on Informatics Conference (p. 16). ACM.
• Lourdusamy, R., & Joseph, M. F. (2016, January). A multilingual ontology for Tamil Literary works. In Advanced Computing and Communication Systems (ICACCS), 2016 3rd International Conference on (Vol. 1, pp. 1-4). IEEE.

[C19] Kanellopoulos D. and Panagopoulos A. (2006) “How semantic web services manage quality of small hospitality businesses?”, International Scientific Congress (24th EuroCHRIE): In Search of Excellence for Tomorrow’s Tourism, Travel & Hospitality.25-28 October 2006, Makedonia Palace Hotel, Thessaloniki, Greece.

• M. Thangaraj, R. Somasundara Manikanda (2011) “A Survey on Semantic Web Based E-Tourism Dynamic Package”, International Journal of Computer Science and Information Technologies, 2(2), 611-613.

• Danica Damljanovic (2007) “Intelligent Web portal in the area of Tourism”. Department of Information Systems, University of Belgrade, Serbia. (MSc Information Systems - Supervisor: Prof. Vladan Devedzic).

[C22] Kanellopoulos D., Kotsiantis S and Tampakas V. (2007) “Towards an ontology-based system for Intelligent Prediction of Firms with Fraudulent Financial Statements”, 12^th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2007) pp.1300-1307, Patras, Greece.

• Dillon D. and Hadzic M. (2009) “A framework for detecting financial statement fraud through multiple data sources”. 3rd IEEE International Conference on Digital Ecosystems and Technologies (DEST apos;09) 1-3 June 2009, pp. 692-696.DOI: 10.1109/DEST.2009.5276674.

[C27]  Kotsiantis S. and Kanellopoulos D. (2008) “Applying machine learning techniques for environmental reporting”. 2008 Fourth IEEE International Conference on Networked Computing and Advanced Information Management, pp.217-223. September 2nd-4th 2008, in Gyeongju, Korea.

• Sonja Fink Babiè, Roberto Biloslavo, (2011) “CORPORATE SUSTAINABILITY REPORTING: OPPORTUNITIES AND CHALLENGES IN A POST-TRANSITION COUNTRY”, Managing Sustainability? Proceedings of the 12th Management International Conference, 2011 Portorož, Slovenia, 23–26 November 2011. 

[C29] Kotsiantis S. and Kanellopoulos D. (2008) “Multi-instance learning for predicting fraudulent financial statements”. International Conference on Convergence and hybrid Information Technology (ICCIT08), pp.448-452, Published by IEEE CS, Nov. 11~13, 2008, Novotel Ambassador Busan, Korea.

• Danenas, P. Garsva, G. (2009) Support vector machines and their application in credit risk evaluation process. Transformations in Business and Economics 8 (3 SUPPL. B), pp.46-58

[C24]   Kotsiantis S. and Kanellopoulos D. (2007) “Local Selective Voting”, International Conference on Convergence Information Technology (IEEE). pp.1621-1626, November 21-23, 2007, in Gyeongju, Korea.

• Peng Zhang, Zhiwang Zhang, Aihua Li and Yong Shi (2008) “Global and Local (Glocal) “Bagging Approach for Classifying Noisy Dataset”. Int J. Software Informatics (Institute of Software, Chinese Academy of Sciences) Vol. 2, No. 2, pp.181-197, Dec. 2008.

Στην εργασία [C32] έχουν αναφερθεί οι:

• Thomas Ng, S., et al. (2011) Applying Z-score model to distinguish insolvent construction companies in China. Habitat International (Elsevier), 35(4), 599-607. Impact Factor: 2.029

Στην εργασία [C33] έχουν αναφερθεί οι:

• Paulius Danevas and Gintautas Garsva (2011) “SVM and XBRL based decision support system for credit risk evaluation”. Available at https://isd.ktu.lt/it2011/material/Proceedings/5_ITA_7.pdf
• Vincas Benevicious et al. (2011) “Application of information technologies to monitor daily physical activities|. pp.159-198, Available at: https://isd.ktu.lt/it2011/material/Proceedings/Information_Technology_Applications.pdf

• HuiXian Tang and YanDong Feng (2011) “An ontology-based model for personalized financial planning product design” 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC) (pp.117–120) Deng Feng, China.

Στην εργασία [Β7] αναφέρονται οι πατέντες:

• Jakob Nielsen (2005) Latency-Reducing Bandwidth –Prioritization for Networks and Clients. No. 6968379 USA PATENT OFFICE, November 22, 2005, https://www.freepatentsonline.com/6968379.html

Στην εργασία [B11] έχουν αναφερθεί οι:

• Akinwale Adio T., Arogundade O.T. and Adebayo F. (2009) “Translated Nigeria stock market prices using artificial neural network for effective prediction”, Journal of Theoretical and Applied Information Technology, Vol. 9, No. 1, pp.36-43.
• Al- Omari, Z. and Abdallah, J. (2008) “Modeling additional operational costs incurred due to absent of the optimal correction in electrical systems”, Journal of Applied Sciences, Vol. 8, No. 23, pp.4422-4427.

[B14]  Kotsiantis S. and Kanellopoulos D. (2007) Combining Bagging, Boosting and Dagging for classification problems. Lecture Notes in Artificial Intelligence. In B. Apolloni et al. (Eds): KES 2007/ WIRN 2007, Part II, LNAI 4963,  pp.493-500, 2007, Springer-Verlag, Heidelberg.

• Krajewski, J., Schnieder, S., Sommer, D., Batliner, A., & Schuller, B. (2012). Applying multiple classifiers and non-linear dynamics features for detecting sleepiness from speech. Neurocomputing, 84, 65-75. Impact Factor: 2.392
• Jakkrit TeCho, Cholwich Nattee, Thanaruk Theeramunkong (2012) Boosting-based ensemble learning with penalty profiles for automatic Thai unknown word recognition. Computers & Mathematics with Applications (Elsevier), 63(6), 1117-1134. Impact Factor: 1.398
• Christopher M. Gifford, Arvin Agah (2010) Collaborative multi-agent rock facies classification from wireline well log data. Engineering Applications of Artificial Intelligence (Elsevier), 23(7), 1158-1172. Impact Factor: 2.368
• Onan, A., Korukoğlu, S., & Bulut, H. (2016). A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification. Expert Systems with Applications, 62, 1-16. ISI Impact Factor (2015):  2.981
• Meddouri, N., Khoufi, H., & Maddouri, M. (2014). Parallel learning and classification for rules based on formal concepts. Procedia Computer Science, 35, 358-367.
• Trabelsi, M., Meddouri, N., Maddouri, M. (2017) A New Feature Selection Method for Nominal Classifier based on Formal Concept Analysis. Procedia Computer Science, vol. 112, issue , year 2017, pp. 186 - 194
• Gifford, C. M., & Agah, A. (2010). Collaborative multi-agent rock facies classification from wireline well log data. Engineering Applications of Artificial Intelligence, 23(7), 1158-1172.
• Gifford, C. M. (2009). Collective machine learning: team learning and classification in multi-agent systems (Doctoral dissertation, University of Kansas).
• Krajewski, J., Batliner, A., & Kessel, S. (2010, August). Comparing multiple classifiers for speech-based detection of self-confidence-A pilot study. In Pattern Recognition (ICPR), 2010 20th International Conference on (pp. 3716-3719). IEEE.
• Lopes, L., Scalabrin, E. E., & Fernandes, P. (2008, April). An empirical study of combined classifiers for knowledge discovery on medical data bases. In Asia-Pacific Web Conference (pp. 110-121). Springer Berlin Heidelberg.
• Fernandes, P., Lopes, L., & Ruiz, D. D. (2010, March). The impact of random samples in ensemble classifiers. In Proceedings of the 2010 ACM Symposium on Applied Computing (pp. 1002-1009). ACM.
• Pham, B. T., Bui, D. T., Prakash, I., & Dholakia, M. B. (2017). Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS. Catena, 149, 52-63.
• Halaby, A., Awad, M., & Khanna, R. (2010, December). Guided Search Space Genetic Programming for identifying energy aware microarchitectural designs. In Energy Aware Computing (ICEAC), 2010 International Conference on (pp. 1-3). IEEE.
• Trabelsi, M., Meddouri, N., & Maddouri, M. (2016). New taxonomy of classification methods based on Formal Concepts Analysis. FCA4AI 2016, 113.
• Okun, O. (2011). Ensembles of Classifiers. In Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations (pp. 252-259). IGI Global.
• Halaby, A.  Awad, M.  Khanna, R. (2010) Guided Search Space Genetic Programming for identifying energy aware microarchitectural designs. Energy Aware Computing (ICEAC), 2010 International Conference on.
• Jarek Krajewski, Anton Batliner, Silke Kessel (2010) Comparing Multiple Classifiers for Speech-Based Detection of Self-Confidence – A Pilot Study. 2010 IEEE International Conference on Pattern Recognition, pp.3716-3719. 
• Lucelene Lopes, Edson Emilio Scalabrin, and Paulo Fernandes (2008) An Empirical Study of Combined Classifiers for Knowledge Discovery on Medical Data Bases. Y. Ishikawa et al. (Eds.): APWeb 2008 Workshops, LNCS 4977, pp.110-121. Springer-Verlag Berlin Heidelberg 2008.

[B18]  Kanellopoulos D. (2009) “High-speed multimedia networks: Critical issues and trends”. Chapter XLIX in Handbook of Research on Telecommunications Planning and Management for Business. pp.775-787. Edited by Prof. In Lee, Western Illinois University, USA.  ISBN: 978-1-60566-194-0, Publisher: Information Science Reference.

• Hasan, M. Z., Al-Rizzo, H., & Al-Turjman, F. (2017). A survey on multipath routing protocols for QoS assurances in real-time wireless multimedia sensor networks. IEEE Communications Surveys & Tutorials, 19(3), 1424-1456. Impact Factor: 17.18

[B23] Kanellopoulos D. (2010) “Adapting multimedia streaming to changing network conditions”. In Ce Zhu, Yuenan Li, Xiamu Niu (Eds.) Streaming Media Architectures, Techniques, and Applications: Recent Advances. Publisher: Information Science Publishing. ISBN: 161692831X

• Narasimha Murthy KN, Y S Kumaraswamy (2011) Robust Model for Text Extraction from Complex Video Inputs Based on SUSAN Contour Detection and Fuzzy C Means Clustering. IJCSI International Journal of Computer Science Issues, Vol. 8, pp. 225-234.
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[B25] Kanellopoulos D. (2015) “Multimedia Social Networks”, In Mehdi Khosrow-Pour (Ed.) Encyclopedia of Information Science and Technology, Third Edition.  Idea Group Inc (IGI). (pp.546-555).

• A. J. Frhan, "Visualization and analysis of user behaviour patterns for multimedia content view in social networks," 2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE), Galati, 2017, pp. 1-7.
  doi: 10.1109/ISEEE.2017.8170685

Στην εργασία [Ε7] έχουν αναφερθεί οι:

• MEDIAPRO Consortium (2005) Deliverable D3.1: “Analyse and Synthesis of the existing data”, May 2005, https://www.mediappro.org/
• Spiliotopoulou-Papantoniou V., Karatrantou A., Panagiotakopoulos C. and Koustourakis G. (2009) Visual representations of the Internet in Greek school textbooks and students’ experiences. Education and Information Technologies (Springer), 14(3), 205-227.

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