Main Citations

The following publications have been cited by other scholars in academic journals and books.


[J64] 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. Special Issue on Multimedia Networking for eCommerce Systems. ISI Impact Factor (2015): 1.275

is cited in:

  • 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. ISI Impact Factor (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. ISI Impact Factor (2015): 0.701
  • Palaiokrassas, G., Voulodimos, A., Konstanteli, K., Vretos, N., Osborne, D. S., Chatzi, E., ... & Varvarigou, T. (2016). DO NOT USE. EXTRA DOI-EH-Social media interaction and analytics for enhanced educational experiences. IEEE MultiMedia. ISI Impact Factor (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)]

[J63]  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

is cited in:

  • 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, 21(8), 2781-2798. ISI Impact Factor: 1.006
  • Razaque, A., & Elleithy, K. (2016). Nomenclature of Medium Access Control Protocol over Wireless Sensor Networks. IETE Technical Review, 33(2), 160-171. ISI Impact Factor (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. ISI Impact Factor (2015): 1.304 
  • Sahoo, A. J., Akhtar, M., & Khusru, A. (2014). Determining the Possibilities and Certainties in Network Participation for MANETS. arXiv preprint arXiv:1401.0875.
  • 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.

[J60]        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.

is cited in:

  • 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

[J56] Balador A., Movaghar A., Jabbehdari S., and Kanellopoulos D. (2012). "A novel contention window control scheme for IEEE 802.11 WLANs". IETE Technical Review, vol.29, issue 3, May-Jun 2012, pp.202-212.

is cited in:
  • Ali, R., Kim, S. W., Kim, B. S., & Park, Y. (2016). Design of MAC Layer Resource Allocation Schemes for IEEE 802.11 ax: Future Directions. IETE Technical Review, 1-25. ISI Impact Factor: 1.304
  • 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.
  • Radha, R., & Kathiravan, D. K. Enhancing the Selection of Backoff Interval Using Fuzzy Logic over Wireless Ad Hoc Networks. The Scientific World Journal, Hindawi Publishing Corporation, 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., Ja'afer, A. S., & Saraireh, S. (2014). A novel adaptive contention window scheme for IEEE 802.11 MAC Protocol. Trends in Applied Sciences Research, 9(6), 275.
  • Jaafer, 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.
  • 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.

[J55]        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

is cited in:

  • 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. [Emerging Source Ciation Indexed]
  • 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.
  • 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. Strategic Customer Relationship Management in the Age of Social Media, 178.

[J41] Lian S., Kanellopoulos D., Ruffo G. (2009) " Recent advances in multimedia information system security ", Informatica. Special Issue on "Multimedia Information System Security", vol. 33, no.1, pp.3-24.

is cited in:

  • 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, 34(5), 1557-1565.
  • Li, L., Yuan, X., Lu, Z., & Pan, J. S. (2010). Rotation invariant watermark embedding based on scale-adapted characteristic regions. Information Sciences, 180(15), 2875-2888.
  • Niu, P. P., Wang, X. Y., Yang, Y. P., & Lu, M. Y. (2011). A novel color image watermarking scheme in nonsampled contourlet-domain. Expert Systems with Applications, 38(3), 2081-2098.
  • Al-Qershi, O. M., & Khoo, B. E. (2013). Passive detection of copy-move forgery in digital images: State-of-the-art. Forensic science international, 231(1), 284-295.
  • Wang, X. Y., Niu, P. P., & Lu, M. Y. (2011). A robust digital audio watermarking scheme using wavelet moment invariance. Journal of Systems and Software, 84(8), 1408-1421.
  • Wang, X. Y., Miao, E. N., & Yang, H. Y. (2012). A new SVM-based image watermarking using Gaussian–Hermite moments. Applied Soft Computing, 12(2), 887-903.
  • Luo, X., Liu, F., Lian, S., Yang, C., & Gritzalis, S. (2011). On the typical statistic features for image blind steganalysis. Selected Areas in Communications, IEEE Journal on, 29(7), 1404-1422.
  • Lian, S., Nikolaidis, N., & Sencar, H. T. (2010). Content-based video copy detection–a survey. In Intelligent Multimedia Analysis for Security Applications (pp. 253-273). Springer Berlin Heidelberg.
  • Rafigh, M., & Moghaddam, M. E. (2010, August). A robust evolutionary based digital image watermarking technique in DCT domain. In Computer Graphics, Imaging and Visualization (CGIV), 2010 Seventh International Conference on (pp. 105-109). IEEE.
  • Lian, S., Chen, X., & Wang, J. (2012). Content distribution and copyright authentication based on combined indexing and watermarking. Multimedia Tools and Applications, 57(1), 49-66.
  • Wang, X. Y., Ma, T. X., & Niu, P. P. (2011). A pseudo-Zernike moment based audio watermarking scheme robust against desynchronization attacks. Computers & Electrical Engineering, 37(4), 425-443.
  • Luo, X., Liu, F., Yang, C., Lian, S., & Zeng, Y. (2012). Steganalysis of adaptive image steganography in multiple gray code bit-planes. Multimedia Tools and Applications, 57(3), 651-667.
  • Lian, S., & Chen, X. (2013). On the design of partial encryption scheme for multimedia content. Mathematical and Computer Modelling, 57(11), 2613-2624.
  • Chen, X., & Lian, S. (2011). Service and P2P based secure media sharing in mobile commerce environments. Electronic Commerce Research, 11(1), 91-101.
  • Shah, J., & Saxena, D. (2011). Video Encryption: A Survey. arXiv preprint arXiv:1104.0800.
  • Shah, J., & Saxena, V. (2011). Performance Study on Image Encryption Schemes. arXiv preprint arXiv:1112.0836.
  • Lian, S., & Chen, X. (2012). Lightweight secure multimedia distribution based on homomorphic operations. Telecommunication systems, 49(2), 187-197.
  • Luo, X., Liu, F., Yang, C., & Lian, S. (2010). Modification ratio estimation for a category of adaptive steganography. Science China Information Sciences, 53(12), 2472-2484.
  • 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.
  • Yang, H. Y., Wang, X. Y., & Ma, T. X. (2011). A robust digital audio watermarking using higher-order statistics. AEU-International Journal of Electronics and Communications, 65(6), 560-568.
  • Lian, S., & Chen, X. (2010). Secure and traceable multimedia distribution for convergent Mobile TV services. Computer Communications, 33(14), 1664-1673.
  • Wang, L., Jiang, X., Lian, S., Hu, D., & Ye, D. (2011). Image authentication based on perceptual hash using Gabor filters. Soft Computing, 15(3), 493-504.
  • Wang, J., & Lian, S. (2012). On the hybrid multi-watermarking. Signal Processing, 92(4), 893-904.
  • Yang, H. Y., Wang, X. Y., & Chen, L. L. (2011). Geometrically invariant image watermarking using SVR correction in NSCT domain. Computers & Electrical Engineering, 37(5), 695-713.
  • 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, 57(3), 453-476.
  • Jeong, S., Lee, E., Lee, S., Chung, Y., & Min, B. (2011, January). Slice-Level selective encryption for protecting video data. In Information Networking (ICOIN), 2011 International Conference on (pp. 54-57). IEEE.
  • Wang, Y., Liu, J., Zhang, W., & Lian, S. (2010). Reliable JPEG steganalysis based on multi-directional correlations. Signal Processing: Image Communication, 25(8), 577-587.
  • 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, 23(6), 892-907.
  • Yu, Z., Wang, C., Thomborson, C., Wang, J., Lian, S., & Vasilakos, A. V. (2012). Multimedia applications and security in mapreduce: opportunities and challenges. Concurrency and Computation: Practice and Experience, 24(17), 2083-2101.
  • 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, 54(2), 341-363.
  • Wójtowicz, A. (2012). Secure User-Contributed 3D Virtual Environments. In Interactive 3D Multimedia Content (pp. 171-193). Springer London.
  • DOUKAS, N. (2012). Low Color-Depth Image Encryption Scheme for use in COTS Smartphones. WSEAS TRANSACTIONS on SYSTEMS, 11, 527-538.
  • Wang, X. Y., Yang, Y. P., & Yang, H. Y. (2009). A novel nonsampled contourlet-domain image watermarking using support vector regression. Journal of Optics A: Pure and Applied Optics, 11(12), 125407.
  • Yang, C., Liu, F., & Luo, X. (2011, November). Error correction of sample pair analysis based on support vector regression. In Multimedia Information Networking and Security (MINES), 2011 Third International Conference on (pp. 633-636). IEEE.
  • Wang, J., & Lian, S. (2012). On multiwatermarking in cloud environment. Concurrency and Computation: Practice and Experience, 24(17), 2151-2164.
  • Lu, J., Huang, Y., Liu, F., & Luo, X. (2011). Pulse position checking-based steganalysis of G. 723.1 compressed speech in VoIP. International Journal of Multimedia Intelligence and Security, 2(3-4), 225-237.
  • Ramirez-Gutierrez, K., Nakano-Miyatake, M., & Perez-Meana, H. (2013). Image authentication using perceptual hashing. Academic Journal Scientific Research and Essays, 8(11), 447-455.
  • Yang, C., Liu, F., Luo, X., & Zeng, Y. (2013). Fusion of Two Typical Quantitative Steganalysis Based on SVR. Journal of Software, 8(3), 731-736.
  • Wang, J., Yan, L., Han, J., & Wang, Y. (2013). Secure hybrid multibit multiplicative watermarking for media distribution over mobile Internet. Security and Communication Networks.
  • Suzuki, K. (2014). U.S. Patent No. 8,713,315. Washington, DC: U.S. Patent and Trademark Office.
  • Dandamwar, T., & Narnaware, M. Real Time and Secure Video Transmission using Open MPI and Open MP.
  • Ojha, V., Sharma, N., Sharma, A., & Jain, S. Information Processing for Multimedia E-Learning Systems.
  • Wójtowicz, A. (2014, January). Mining in Dynamically Composed Scripted 3D Scenes for Better Access Control–Computational Evaluation. In International Joint Conference SOCO’14-CISIS’14-ICEUTE’14 (pp. 423-432). Springer International Publishing.
  • Lonarkar, M. G., & Pandey, Y. Real Time & Secure Video Transmission Using OpenMPI.
  • Abraham, J. (2011). Gray Scale Image Watermarking using LSB Modification. International Journal of Advanced Research in Computer Science, 2(5).
  • Barnes, J. A Survey of Recent Advances in Video Security.
  • Wu, C. M., Hu, Y. C., Liu, K. Y., & Chuang, J. C. (2014). A Novel Active Image Authentication Scheme for Block Truncation Coding. International Journal of Signal Processing, Image Processing & Pattern Recognition, 7(5).
  • Wu, C. M., Hu, Y. C., Liu, K. Y., & Chuang, J. C. (2014). A Novel Active Image Authentication Scheme for Block Truncation Coding. International Journal of Signal Processing, Image Processing & Pattern Recognition, 7(5).
  • Zhang, X., & Wang, Z. J. (2013, November). Correlation-and-bit-aware multiplicative spread spectrum embedding for data hiding. In Information Forensics and Security (WIFS), 2013 IEEE International Workshop on (pp. 186-190). IEEE.
  • Zheng, D., Liu, F., Yang, C., Zhang, Q., & Luo, X. (2011). Identification of steganography software based on register dependence. International Journal of Multimedia Intelligence and Security, 2(3-4), 339-350.
  • Mármol, F. G., Alcañiz, L. D. O., NEC, D. A., Rozinaj, G., Labaj, O., Schumann, S., ... & Vanattenhoven, J. (2012). Deliverable D3.
  • Niu, P., Wang, X., & Lu, M. (2011). A novel pyramidal dual-tree directional filter bank domain color image watermarking algorithm. In Information and Communications Security (pp. 158-172). Springer Berlin Heidelberg.
  • Yang, H. Y., Chen, L. L., & Wang, X. Y. (2011). A content-based digital image watermarking scheme resistant to local geometric distortions. Journal of Optics, 13(1), 015404.
  • Satao, M. V. P. E-Resource for Technical Institute & Engineering Colleges a Boon to libraries & information Centers in India.
  • Perez, M. P., Fujiyoshi, M., & Kiya, H. (2010, October). A codestream domain authentication and tamper localization scheme for JPEG 2000. In Communications and Information Technologies (ISCIT), 2010 International Symposium on (pp. 810-814). IEEE.
  • Abraham, J., & Paul, V. (2014, July). Image watermarking using DCT in selected pixel regions. In Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on (pp. 398-402). IEEE.
  • Qureshi, A., Megías, D., & Rifà-Pous, H. (2015). Framework for preserving security and privacy in peer-to-peer content distribution systems. Expert Systems with Applications, 42(3), 1391-1408.
  • Liu, Y., Wang, Y., & Zhu, X. (2014). Novel robust multiple watermarking against regional attacks of digital images. Multimedia Tools and Applications, 1-23.
  • Btoush, M. H., Khatatneh, K. F., Al-Talaq, Q. A., Abdulah, P., & Gazi, B. (2013). Multi-Cipher Single Message Encryption Algorithm. International Journal of Computer Applications, 73(8).
  • Dhall, S., Pal, S. K., & Sharma, K. (2014, December). Improvised block cipher customized for multimedia security. In Power India International Conference (PIICON), 2014 6th IEEE (pp. 1-5). IEEE.
  • Zhang, X., Wang, Z. J., & Wang, X. (2014). Correlation-and-bit-aware additive spread spectrum data hiding for Laplacian distributed host image signals. Signal Processing: Image Communication, 29(10), 1171-1180.
  • Abraham, J. Digital Watermarking for Safeguarding Video Broadcasts in Media.
  • Liu, G., & Liu, W. (2011). An adaptive matrix embedding based on LSB matching for grey-scale images. International Journal of Multimedia Intelligence and Security, 2(3-4), 238-251.
  • Xiao, C., Wang, L., & Zhu, M. (2015). A resource-efficient multimedia encryption scheme for embedded video sensing system based on unmanned aircraft. Journal of Network and Computer Applications.
  • Wang, X., Liu, F., & Luo, X. (2010, March). A Novel Concatenated Fingerprint Code for Multimedia. In Education Technology and Computer Science (ETCS), 2010 Second International Workshop on (Vol. 3, pp. 169-172). IEEE.


[J35] Kanellopoulos D. (2008) "An ontology-based system for intelligent matching of travellers' needs for group package tours", International Journal of Digital Culture and Electronic Tourism (Inderscience Publishers) vol. 1, no.1, pp.76-99. DOI: 10.1504/IJDCET.2008.020136

is cited in:

  • García-Crespo, A., Chamizo, J., Rivera, I., Mencke, M., Colomo-Palacios, R., & Gómez-Berbís, J. M. (2009). SPETA: Social pervasive e-Tourism advisor. Telematics and Informatics, 26(3), 306-315.
  • García-Crespo, Á., López-Cuadrado, J. L., Colomo-Palacios, R., González-Carrasco, I., & Ruiz-Mezcua, B. (2011). Sem-Fit: A semantic based expert system to provide recommendations in the tourism domain. Expert systems with applications, 38(10), 13310-13319.
  • Zhang, Z., Lin, H., Liu, K., Wu, D., Zhang, G., & Lu, J. (2013). A hybrid fuzzy-based personalized recommender system for telecom products/services. Information Sciences, 235, 117-129.
  • Shambour, Q., & Lu, J. (2011). A hybrid trust‐enhanced collaborative filtering recommendation approach for personalized government‐to‐business e‐services. International Journal of Intelligent Systems, 26(9), 814-843.
  • Choi, C., Cho, M., Choi, J., Hwang, M., Park, J., & Kim, P. (2009, May). Travel ontology for intelligent recommendation system. In Modelling & Simulation, 2009. AMS'09. Third Asia International Conference on (pp. 637-642). IEEE.
  • Lu, J., Shambour, Q., Xu, Y., Lin, Q., & Zhang, G. (2013). A WEB‐BASED PERSONALIZED BUSINESS PARTNER RECOMMENDATION SYSTEM USING FUZZY SEMANTIC TECHNIQUES. Computational Intelligence, 29(1), 37-69.
  • 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.
  • Park, H., Kwon, S., & Kwon, H. C. (2009, December). Ontology-based approach to intelligent ubiquitous tourist information system. In Ubiquitous Information Technologies & Applications, 2009. ICUT'09. Proceedings of the 4th International Conference on (pp. 1-6). IEEE.
  • 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.
  • 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.
  • 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). An Ontology-Based Context-Aware Mobile System for On-the-Move Tourists. In Evolving Ambient Intelligence (pp. 252-256). Springer International Publishing.
  • 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.
  • 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.
  • Komkid, C. (2013). The design of a mobile engine for personalized tourist attraction recommendation using social networking services.
  • 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.

[J26] Kanellopoulos D., Sakkopoulos E., Lytras M., Tsakalidis A. (2007) "Using web-based teaching interventions in computer science courses", IEEE Transactions on Education, Special Issue: Open-Source Software, vol. 50, no. 4, pp.338-344. DOI: 10.1109/TE.2007.906906

is cited in:
  • Lytras, M. D., & García, R. (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, 4(1), 93-108.
  • Vargas-Vera, M., & Lytras, M. D. (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, 4(1), 1-17.
  • Mark, K. P. (2009). Technology Support for Engagement Retention: The Case of BackPack. Knowledge Management & E-Learning: An International Journal (KM&EL), 1(3), 163-179.
  • 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.
  • Mark, K. P., & Vogel, D. R. (2009). An Exploratory Study of Personalization and Learning Systems Continuance. PACIS 2009 Proceedings, 34.
  • Sakkopoulos, E., Costopoulou, C. I., Ntaliani, M. S., Liopa-Tsakalidis, A., & Sideridis, A. B. (2011). An Architecture of m-Learning Environment for Medicinal and Aromatic Plants. Journal of Information Technology in Agriculture, 4(1).
  • Han, J., Hu, W., & Feng, X. (2008, November). Exploration and Practice on Teaching Java as Introductory Language for Non-CSE Major Students. In Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for (pp. 2696-2700). IEEE.
  • Oginga, R. A., & Karie, N. M. (2014). Evaluating Moodle As An Open Source E-Learning Software Tools For Teaching In Tertiary Institutions.


[J8]  Kotsiantis S., Kanellopoulos D., Pintelas, P. (2006) "Data preprocessing for supervised leaning". International Journal of Computer Science, Vol. 1, No. 2, pp.111-117.

is cited in:

  • 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), Vol. 128, No. 2, pp. 614-624
  • 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, "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.
  • 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 (Professional Engineering Publishing) Vol. 224, No. 3, pp. 453-463. doi: 10.1243/09544119JEIM642.
  • Jan Carlos Barca (2009) “New Multicolour Illuminated Contour-based Markers and their use in Motion Capture”, PhD Thesis, Monash University. Australia.
  • Jha, S.K.; Yadava, R.D.S.; "Preprocessing of SAW Sensor Array Data and Pattern Recognition," Sensors Journal, IEEE , vol.9, no.10, pp.1202-1208, Oct. 2009 doi: 10.1109/JSEN.2009.2029452
  • Mikael Kuusela, Jerry W. Lämsä, Eric Malmi, Petteri Mehtälä and Risto Orava  (2009) “Multivariate Techniques for Identifying Diffractive Interactions at the LHC”. [Online:]
  • 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.

[J9]  Kanellopoulos D. (2006) "The advent of semantic web in tourism information systems". Tourismos: An International Multidisciplinary Journal of Tourism, Vol. 1, No. 2,  pp.75-91 (Autumn 2006, ISSN: 1790-8418)

is cited in:

  • 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:
  • Garcia-Barriocanal E. and Sicilia M.-A. (2008) “On linking cultural spaces and e-Tourism: An ontology-based approach”. In M.D. Lytras et al. (Eds): WSKS 2008, CCIS 19, pp.694-701, Springer-Verlag Berlin Heidelberg.
  • 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).

[J10]  Kanellopoulos D., Panagopoulos A. (2008) "Exploiting tourism destinations' knowledge in an RDF-based P2P network". Journal of Network and Computer Applications (Elsevier Science), Vol. 31, No. 2, pp.179-200.

is cited in:

  • Meirong Liu, Timo Koskela, Zhonghong Ou, Jiehan Zhou, Jukka Riekki and Mika Ylianttila (2011) “Super-peer-based coordinated service provision”. Journal of Network and Computer Applications (Elsevier Science) In Press, Corrected Proof.
  • 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.
  • 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.

[J11] 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, Vol. 2, No. 4, pp.75-95 (ISSN: 1790-3254-4).

is cited in:

  • Lazarinis F., Green S. and Pearson E. (2008) “Measuring the conformance of hypermedia assessment tools to QTI”, International Journal of Innovation and Learning (Inderscience Publishers), Vol. 6, No. 2, pp.127-146.

[J12]  Kanellopoulos D., Kotsiantis S., Pintelas P. (2006) "Intelligent knowledge management for the travel domain". GESTS International Transactions on Computer Science and Engineering, Vol. 30, No. 1, pp.95-106 (April 30, ISSN: 1738-6438).

is cited in:

  • Juana Marıa Ruiz-Martınez, Dagoberto Castellanos-Nieves, Rafael Valencia-Garcıa, Jesualdo Tomas Fernandez-Breis, Francisco Garcıa-Sanchez, Pedro Jose Vivancos-Vicente, Juan Salvador Castejon-Garrido, Juan Bosco Camon, and Rodrigo Martınez-Bejar (2009) “Accessing Touristic Knowledge Bases through a Natural Language Interface”. D. Richards and B.-H. Kang (Eds.): PKAW 2008, LNAI 5465, pp.147–160, 2009. Springer-Verlag Berlin Heidelberg 2009.
  • Damljanovic D., Devedzic V. (2009) “Semantic Web and e-tourism”. In Mehdi Khosrow-Pour (Ed.) Encyclopedia of Information Science and Technology, Vol. VII, 2nd 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).
  • 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).

[J13]  Kotsiantis S., Kanellopoulos D., Pintelas P. (2006)"Handling imbalanced datasets: a review". GESTS International Transactions on Computer Science and Engineering, Vol. 30, No. 1, pp.25-36 (April 30, ISSN:1738-6438)

is cited in:

  • Zhongming Ma, Gautam Pant and Olivia R.L. Sheng (in press). “Mining competitor relationships from online news: A network-based approach”. Electronic Commerce Research and Applications, (Elsevier).
  • Garcia-Moral, A.I.; Solera-Urena, R.; Pelaez-Moreno, C.; Diaz-de-Maria, F. (2011) “Data Balancing for Efficient Training of Hybrid ANN/HMM Automatic Speech Recognition Systems”, IEEE Transactions on Audio, Speech, and Language Processing, 19(3): 468 – 481.
  • Jinchang Ren, Dong Wang, and Jianmin Jiang (2011) “Effective recognition of MCCs in mammograms using an improved neural classifier”. Engineering Applications of Artificial Intelligence (Elsevier Science), Vol. 24, Issue 4, pp. 638-645.
  • DING, ZEJIN (2011) “DIVERSIFIED ENSEMBLE CLASSIFIERS FOR HIGHLY IMBALANCED DATA LEARNING AND THEIR APPLICATION IN BIOINFORMATICS”. Computer Science Department, Georgia State University. Computer Science Dissertations. Paper 60.
  • Leandro L. Minku, Xin Yao, (2011) "DDD: A New Ensemble Approach For Dealing With Concept Drift," IEEE Transactions on Knowledge and Data Engineering, 16 Feb. 2011. IEEE computer Society Digital Library. IEEE Computer Society,
  • Kehan Gao, Taghi M. Khoshgoftaar and Naeem Seliya (2011) “Predicting high-risk program modules by selecting the right software measurements”. Software Quality Journal (Springer).
  • David Martinez, Timothy Baldwin (2011) “Word sense disambiguation for event trigger word detection in biomedicine”, BioMedCentral Bioinformatics 2011, 12(Supp 2):S4.
  • Wen Zhang; Juan Liu; Yanqing Niu; Qingjiao Li; Zijing Hui (2010) “Predicting cleavage sites in exogenous antigen using weighted SVM”, 2010 2nd International Conference on Computer Engineering and Technology (ICCET), 16-18 April 2010. pp. V1-478 - V1-482.
  • Giovanna Menardi, Nicola Torelli (2010) “Training and assessing classification rules with unbalanced data”. Working Paper Series, N.2, 2010.
  • Addis, A.  Armano, G.  Vargiu, E (2010) “Using Progressive Filtering to Deal with Information Overload”. In 2010 Workshop on Database and Expert Systems Applications (DEXA). Aug. 30 2010-Sept. 3 2010. pp.20-24.  Location: Bilbao ISSN: 1529-4188.
  • Yanping Yang, Guangzhi Ma (2010) “Ensemble-based active learning for class imbalance problem”, J. Biomedical Science and Engineering, 2010, 3, pp. 1022-1029.
  • Asrul Adam et al. (2010) “A Modified Artificial Neural Network Learning Algorithm for Imbalanced Data Set Problem”. 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks.
  • Apoorv Agarwal and Owen Rambow (2010) “Automatic detection and classification of social events”. Proc. of the 2010 Conference on Empirical Methods in Natural Language Processing, Cambridge, Massachusetts, pp.1024-1034.
  • Garcia-Moral, A. I.; Solera-Urena, R.; Pelaez-Moreno, C.; Diaz-de-Maria, F.; , "Data Balancing for Efficient Training of Hybrid ANN/HMM Automatic Speech Recognition Systems," Audio, Speech, and Language Processing, IEEE Transactions on , vol.PP, no.99, pp.1-1, 0 doi: 10.1109/TASL.2010.2050513
  • Zhang, Wen; Liu, Juan; Niu, Yanqing; Qingjiao Li; Zijing Hui (2010) "Predicting cleavage sites in exogenous antigen using weighted SVM," 2010 2nd International Conference on Computer Engineering and Technology (ICCET), vol.1, no., pp.V1-478-V1-482, 16-18 April 2010 doi: 10.1109/ICCET.2010.5486025.
  • Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer (2010) “Detecting and ordering salient regions”, Data Mining and Knowledge Discovery (Springer), DOI: 10.1007/s10618-010-0194-6.
  • A. Addis et al. (2010) “Using the progressive filtering approach to deal with imbalance in Large-scale taxonomies”, Large Scale Hierarchical Text classification  (LSHTC) 32nd European Conference on Information Retrieval (ECIR).
  • Wallace Byron, Trikalinos Thomas, Lau Joseph,  Brodley Carla, Schmid Christopher (2010) “Semi-automated screening of biomedical citations for systematic reviews”, BMC Bioinformatics, Vol. 11, No. 1.
  • Si Chen, Gongde Guo, Lifei Chen (2010) “A New Over-Sampling Method Based on Cluster Ensembles," 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, pp. 599-604, 20-23 April 2010. doi: 10.1109/WAINA.2010.40
  • Wang S. and Yao X. (2009) “Theoretical study of the relationship between diversity and single-class measures for class imbalance learning”. Proceedings of the 2009 IEEE International Conference on Data Mining Workshops, (pp.76-81). ISBN:978-0-7695-3902-7. Publisher : IEEE Computer Society
  • 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.
  • Jyhshyan Lan, Michael Y. Hu, Eddy Patuwo, G. Peter Zhang, (2009) “An investigation of neural network classifiers with unequal misclassification costs and group sizes”, Decision Support Systems (Elsevier Science Publishers) Vol. 48, No. 4, pp.582-591
  • Julia Bondarenko (2009) “Oversampling under Statistical Criteria: Example of Daily Traffic Injuries Number”. Contemporary Engineering Sciences, Vol. 2, No. 6, pp. 249-264.
  • Duemong Fudailah, Preechaveerakul Ladda, and Vanichayobon Sirirut (2009) “FIAST: A Novel Algorithm for Mining Frequent Itemsets”, 2009 IEEE International Conference on Future Computer and Communication, pp.140-144, 3-5 April 2009.
  • 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.
  • Lieweab Cheng, Su-Chuan Chen and Jashen Chen (2009) “Applying weighted association rules with the consideration of product item relevancy”, 6th International Conference on Service Systems and Service Management ICSSSM 09, pp.888-893, 8-10 June 2009.
  • Biddiss E., Brownsell S. and Hawley M.S. (2009) “Predicting need for intervention in individuals with congestive heart failure using a home-based telecare system”, Journal of Telemedicine and Telecare (Elsevier Publishers), Vol. 15, No. 5, pp.226-231.
  • Nguyen Thai-Nghe, Andre Busche and Lars Schmidt-Thieme (2009) “Improving Academic Performance Prediction by Dealing with Class Imbalance”. 9th IEEE International Conference on Intelligent Systems Design and Applications (ISDA 2009), Pisa, Italy.
  • Alejandro Hadad, Diego Evin y Bartolomé Drozdowicz, (2008) “Modelo para el Tratamiento de Datos Desbalanceados basado en Redes Neuronales Autoorganizadas”, XVII CONGRESO ARGENTINO DE BIOINGENIERIA, VI JORNADAS DE INGENIERIA CLINICA.
  • Shu-Xue Zou, Yanxin Huang, Yan Wang, Chunguang Zhou (2008) “A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy”, Journal of Bionic Engineering (Elsevier Science), Vol. 5, pp. 215-223.
  • Vegard Engen, Jonathan Vincent and Keith Phalp (2008) “Enhancing network based intrusion detection for imbalanced data”. International Journal of Knowledge-based and Intelligent Engineering Systems (IOS Press), Vol. 12, pp.357-367.
  • Xinjian Guo, Yilong Yin, Cailing Dong, Gongping Yang, Guangton Zhou (2008) “On the Class Imbalance Problem”. ICNC '08, Fourth International Conference on Natural Computation, Vol. 4, pp.192-201. Location: Jinan.
  • Simon Marcellin (2008) “Arbres de decision en situation d'asymetrie”, PhD Thesis, University Lumiere Lyon II, Ecole Doctorale Informatique et information pour la Societe, France.
  • Zhongming Ma, Olivia R. Liu Sheng, Gautam Pant (2007) “A Network Approach to Automatically Discovering Competitor Relationships from Business News”, Technical Report, David Eccles School of Business The University of Utah, 2007.
  • Shu-Xue Zou, Yanxin Huang, Yan Wang, Chengquan Hu, Yanchun Liang, Chunguang Zhou (2007) “A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy”, Advances in Neural Networks – ISNN 2007, Lecture Notes in Computer Science, pp.1264-1272.
  • Shoemaker, L., Banfield, R. O., Hall, L., Bowyer, K. and Kegelmeyer, P. (2007) “Using classifier ensembles to label spatially disjoint data”. Information Fusion (Elsevier Science) Vol. 9, No. 1, pp.120-133.
  • M. Karagiannopoulos, D. Anyfantis, S. Kotsiantis and P. Pintelas, (2007) “Local Cost Sensitive Learning For Handling Imbalanced Data Sets”, 15th IEEE Mediterranean Conference on Control and Automation. 27-30 June, 2007 Athens, Greece, CD Proceedings.
  • 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.

[J15]  Kotsiantis S., Kanellopoulos D., Pintelas P. (2006) "Local boosting of decision stumps for regression and classification problems", International Journal of Computers, Vol. 1, No. 4, pp.30-37 (July 2006, ISSN: 1796-203X).

is cited in:

  • Marom, N.D.  Rokach, L.  Shmilovici, A. (2010) “Using the confusion matrix for improving ensemble classifiers”. In Proc. IEEE 26th Convention of Electrical and Electronics Engineers in Israel (IEEEI). 17-20 Nov. 2010, Eliat, Israel, pp. 555-559.
  • M. Carmen Garrido, Jose M. Cadenas, Piero, P. Bonissone (2010) “A classification and regression technique to handle heterogeneous and imperfect information”. Soft Computing - A Fusion of Foundations, Methodologies and Applications (Springer-Verlag) Vol. 14, No. 11, pp.1165-1185.
  • Mrutyunjaya Panda and Manas Ranjan Patra (2009) “Meta classifiers for building an efficient network intrusion detection system”. IJCSS, Vol. 4, No. 4., pp.
  • Rokach, L. (2009) “Collective-agreement-based pruning of ensembles”. Computational Statistics and Data Analysis (Elsevier Science Publishers), Vol. 53, No. 4, pp.1015-1026.
  • Masanori Kawakita, and Sjinto Eguchi (2008) “Boosting method for local learning in statistical pattern recognition”. Neural Computation (MIT Press), Vol. 20, No. 11, pp.2792-2838.
  • Eric Craig and Falk Huettmann (2008) “Using Blackbox Algorithms Such as TreeNEt and Random Forests for Data - Mining and for Finding Meaningful Patterns, Relationships, and Outliers in Complex Ecological Data: An Overview, an Example Using Golden Eagle Satellite Data and an Outlook for a Promising Future”, pp.65. In Intelligent Data Analysis. Developing New Methodologies through Pattern Discovery and Recovery. (Edited by Hsiao-Fan Wang). 


[J16] Kotsiantis S., Kanellopoulos D. (2006) "Association rules mining: A recent overview, GESTS International Transactions on Computer Science and Engineering, Vol. 32, No. 1, pp.71-82 (July 30, 2006. ISSN: 1738-6438)

is cited in:

  • Serkan Altuntas and Hasan Selim (in press) “Facility layout using weighted association rule-based data mining algorithms: Evaluation with simulation”, Expert Systems with Applications (Elsevier)
  • 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.
  • 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.
  • 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, July 2010. 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
  • Chidansh Amitkumar Bhatt and Mohan S. Kankanhalli (2010) “Multimedia data mining: state of the art and challenges”. Multimedia Tools and Applications. DOI: 10.1007/s11042-010-0645-5Online First.
  • 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.
  • 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), Vol. 37, No. 12., pp. 8079-8089. December 2010.
  • 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.
  • Rakhi Garg and P.K. Mishra (2010) “Parallel Association Rule Mining on Heterogeneous System”, International Journal of Computer Application, Vol. 1, No. 14, pp.87-91.
  • Tim Schluter and Stefan Conrad (2010) “Mining several kinds of temporal association rules enhanced by tree structures”, eknow, pp.86-93, 2010 Second International Conference on Information Process, and Knowledge Management, 2010.
  • 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 Science) Vol. 7, No. 3, pp.187-209.
  • Zahoor ur Rehman, Muhammad Imran Sarwar, Muhammad Aslam, Muhammad Shaheen (2009) “An intelligent assistant for mathematical production”, Proceedings of the 6th International Conference on Frontiers of Information Technology, Abbottabad, Pakistan.
  • Liu Yongmei; Guan Yong; (2009) "Application in Market Basket Research Based on FP-Growth Algorithm," Computer Science and Information Engineering, 2009 WRI World Congress on, vol.4, no., pp.112-115, March 31, 2009-April 2 2009.  doi: 10.1109/CSIE.2009.1073
  • 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.
  • Lisa Fan and Minxiao Lei (2009) Reducing cognitive overload by meta-learning assisted algorithm selection (Chapter 3) pp.36-51. In Discovering and breakthroughs in cognitive informatics and natural intelligence. Editor: Yingxu Wang, IGI Global
  • Shankar S. and Purusothaman T. (2009) “A novel utility sentient approach for mining interesting association rules”, ISAST Transactions on Computers and Intelligent Systems, Vol. 1, No. 1, pp.50-55.
  • Robertas Damasevicius (2009) “Analysis of Academic Results for Informatics course improvement using Association Rule Mining” G.

[J6]  Kotsiantis S., Kanellopoulos D., Tampakas V. (2006) "On implementing a financial decision support system". International Journal of Computer Science and Network Security, Vol. 6, No. 1A, pp.103-112.

is cited in:

  • Antonio Wong, Pak-Lok Poon (2009) “Using Information Technologies to Restore Investor Trust”, ISACA Journal, Vol. 5, pp.1-5.
  • Kirkos E., Spathis C. and Manolopoulos Y. (2008) “Support vector machines, Decision Trees and Neural networks for auditor selection”. Journal of Computational Methods in Sciences and Engineering (IOS Press), Vol. 8, No. 3, pp.213-224.

 [J5] Kanellopoulos D., Kotsiantis S., Pintelas P. (2006) "Considering the Educational Semantic Web". Themes in Education, Vol. 7, No. 2, pp.145-164.

is cited in:

  • 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), Vol. 8, No. 3, pp.163-182.
  • Stavrinoudis D. and Xenos M. (2008) “On technological issues affecting online learners' behaviour.” Journal of Computational Methods in Sciences and Engineering (IOS Press), Vol. 8, No. 3, pp.183-194.
  • Togias K. (2007) “Learning content Ontology Evaluation, Master Thesis, Department of Mathematics, University of Patras, Greece.

[J4]  Sakkopoulos E., Kanellopoulos D., Tsakalidis A. (2006) "Semantic mining and web service discovery techniques for media resources management". International Journal of Metadata, Semantics and Ontologies (Inderscience Publishers), Vol. 1, No. 1, pp.66-75.

is cited in:

  • 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. 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), Vol. 1, No. 1, pp.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).
  • 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.
  • 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
  • Makripoulias Y., Makris C., Sakkopoulos E., Panagis Y., Adamopoulou P. and Tsakalidis A. (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.


[J2]  Kanellopoulos D., Panagopoulos A., Psillakis Z. (2004) "Multimedia applications in Tourism: The case of travel plans". Tourism Today, No. 4, pp.146-156.

is cited in:

  • 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:
  • 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).
  • 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.

[J1]   Kotsiantis S., Kanellopoulos D., Pintelas P. (2004) "Multimedia mining". WSEAS Transactions on Systems, Vol. 3, No. 10, pp.3263-3268.

is cited in:

  • Vijayakumar, V., & Nedunchezhian, R. (2012). A study on video data mining. International journal of multimedia information retrieval, 1(3), 153-172.
  • Goele, S., & Chanana, N. (2012). Data Mining Trend In Past, Current And Future. International Journal of Computing & Business Research, In Proc. I-Society.

  • Venkatadri, M., & Lokanatha, C. R. (2011). A review on data mining from past to the future. International Journal of Computer Applications, 15(7), 19-22.
  • Manjunath, T. N., Hegadi, R. S., & Ravikumar, G. K. (2010). A Survey on Multimedia Data Mining and Its Relevance Today. IJCSNS, 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).
  • Mirończuk, M., & Maciak, T. (2009). Eksploracja Danych w kontekście procesu Knowledge Discovery In Databases (KDD) i metodologii Cross-Industry Standard Process for Data Mining (CRISP-DM). Metody Informatyki Stosowanej, 65-79.
  • Paidi, A. N. (2012). Data Mining: Future Trends and Applications. International Journal of Modern Engineering Research (IJMER) Vol, 2, 4657-4663.
  • Mirończuk, M. (2010). Przegląd i klasyfikacja zastosowań, metod oraz technik eksploracji danych. Studia i Materiały Informatyki Stosowanej, (2), 35-46.
  • Guleria, P., & Sood, M. (2014). DATA MINING IN EDUCATION: AReview ON THE KNOWLEDGE DISCOVERY PERSPECTIVE. International Journal Of Data Mining & Knowledge Management Process, 4(5).
  • Kapoor, A. (2014). Data Mining: Past, Present and Future Scenario. International Journal of Emerging Trends & Technology in Computer Science, 3(1), 95-99.
  • Manickam, R., Boominath, D., & Bhuvaneswari, V. (2012). An Analysis Of Data Mining: Past, Present and Future. International journal of Computer Engineering & Technology (IJCET), 3(1), 1-9.
  • Singh, L. (2013). Data Mining: Review, Drifts and Issues. International Journal of Advance Research and Innovation, 2, 44-48.
  • Semaan, G. S., ANDREI, D. A. G., & Dias, C. R. Descoberta de Associações em Dados. Faculdade Metodista Granbery.
  • 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, 3(4).
  • Shambharkar, P., Srivastava, N., Yadav, A., Sharma, A., & Katiyar, A. (2012). A Survey on Classification of Videos using Data Mining Techniques. IJCA Special Issue on Issues and Challenges in Networking, Intelligence and Computing Technologies, (5), 27-32.
  • Vijayarani, S., & Sakila, A. (2015). MULTIMEDIA MINING RESEARCH–AN OVERVIEW. International Journal of Computer Graphics & Animation, 5(1), 69.
  • Months, E. S. State of the Art Report on Multimedia Mining.
  • 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.
  • Kate, A. V., Nikilav, P. V., Giriesh, S., & Naren, J. Multimedia Data Mining-A Survey.
  • Kumar, A. (2014). Data Mining: Pattern and Trends by Using Biocomputers.
  • Samoilenko, N., & Nahar, N. (2013, July). IT tools for knowledge storage and retrieval in globally distributed complex software and systems development of high-tech organizations. In Technology Management in the IT-Driven Services (PICMET), 2013 Proceedings of PICMET'13: (pp. 1353-1369). 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.
  • 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).
  • Semaan G.S., Graca A.A., Dias C.R. (2006) Descoberta de associações em dados”. Revista electronica de Faculdade Medotista Granbery, , 01 Sept. 2006.
  • 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.

[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.

is cited in:

  • 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., 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.
  • Bodea, C. N. (2007, August). An innovative system for learning services in project management. In Service Operations and Logistics, and Informatics, 2007. SOLI 2007. IEEE International Conference on (pp. 1-5). IEEE.
  • Bodea, C. N. (2009). Project management competences development using an ontology-based e-learning platform (pp. 31-39). Springer Berlin Heidelberg.
  • Falcidieno, B., Pitikakis, M., Spagnuolo, M., Vavalis, M., & Houstis, C. (2008). FOCUS K3D: Promoting the use of knowledge intensive 3D media. In 14th International Conference on Virtual Systems and Multimedia Dedicated To Digital Heritage (pp. 20-26).
  • Dag, F., & Erkan, K. (2007). Realizing the Personalized Learning Paths in a LMS. Online Submission.
  • Oprea, M. (2013). A General Framework for Educational Ontologies Development. International Journal of Computer Science Research and Application, 3(2), 12-22.
  • Morioka, T., Iwane, N., & Matsubara, Y. (2007). A Study on Building of Japanese History Ontology Aiming at Learning Support. FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS, 162, 109.
  • Nicoleta, B. C. (2007). Ontology-Based Learning in Project Management. In ECEL 2007: 6th European Conference on E-Learning: Copenhagen Business School, Denmark, 4-5 October 2007 (p. 119). Academic Conferences Limited.
  • Kaur, G., & Chaudhary, D. (2015). Semantic Web: A Boon for E-learning. development, 4(7).
  • 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.
  • Bodea, C. N., Dworatschek, S., Nehlsen, T., Gatzmaga, I., Mihić, M., Petrović, D., ... & Steyn, P. Projektna mreža Slovenije.
  • Gonçalves, G. C. (2008). Construção de ontologia para suporte cognitivo a um ambiente de aprendizagem.
  • Fróes, M. F., & Santos, E. R. E-BIACS: Um Sistema para a Construção de Ambientes Virtuais para Aprendizagem Baseada em Problemas. RENOTE, 12(1).
  • Raby, T., & Ravaut, F. Utilisation d’ontologies dans une application médicale décisionnelle.
  • BODEA, V., SABAU, G., & SANDU, D. (2007). E-Learning–A Solution For Project Management Excellence. Projektna mreža Slovenije, 35.

[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 3rd 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.

is cited in:
  • Butler, L. J. (2003). U.S. Patent No. 6,584,493. Washington, DC: U.S. Patent and Trademark Office.
  • Dubrow, D. L., Butler, L. J., Dailey, J. L., & Giloi, C. T. (2003). U.S. Patent No. 6,570,590. Washington, DC: U.S. Patent and Trademark Office.
  • Liles, J. R., & Giloi, C. T. (2005). U.S. Patent No. 6,851,053. Washington, DC: U.S. Patent and Trademark Office.
  • Butler, L. J. (2006). U.S. Patent No. 7,136,062. Washington, DC: U.S. Patent and Trademark Office.
  • Butler, L. J. (2007). U.S. Patent No. 7,167,182. Washington, DC: U.S. Patent and Trademark Office.
  • Giloi, C. T., MacLin, M. F., & Morris, M. G. (2005). U.S. Patent No. 6,850,985. Washington, DC: U.S. Patent and Trademark Office.
  • Owen, J. E., Diaz, R. Z., & Colavin, O. (2008). U.S. Patent No. 7,321,368. Washington, DC: U.S. Patent and Trademark Office.
  • Owen, J. E., Diaz, R. Z., & Colavin, O. (2009). U.S. Patent No. 7,542,045. Washington, DC: U.S. Patent and Trademark Office.
  • Giloi, C. T., Maclin, M., & Morris, M. G. (2014). U.S. Patent No. 8,631,074. Washington, DC: U.S. Patent and Trademark Office.