Home Nonfiction 7 • Download e-book for kindle: Adaptive and Personalized Semantic Web by Christos Makris, Yannis Panagis (auth.), Spiros Sirmakessis

Download e-book for kindle: Adaptive and Personalized Semantic Web by Christos Makris, Yannis Panagis (auth.), Spiros Sirmakessis

By Christos Makris, Yannis Panagis (auth.), Spiros Sirmakessis Dr. (eds.)

ISBN-10: 3540306056

ISBN-13: 9783540306054

ISBN-10: 3540332790

ISBN-13: 9783540332794

Web Personalization could be outlined as any set of activities which can tailor the internet event to a specific person or set of clients. to accomplish potent personalization, enterprises needs to depend on all on hand information, together with the utilization and click-stream facts (reflecting person behaviour), the positioning content material, the location constitution, area wisdom, in addition to person demographics and profiles. additionally, effective and clever ideas are had to mine this knowledge for actionable wisdom, and to successfully use the found wisdom to augment the clients' net event. the purpose of the overseas Workshop on Adaptive and custom-made Semantic internet that used to be held within the 16th ACM convention on Hypertext and Hypermedia (September 6-9, 2005, Salzburg, Austria) was once to assemble researchers and practitioners within the fields of net engineering, adaptive hypermedia, semantic net applied sciences, wisdom administration, details retrieval, person modelling, and different comparable disciplines which offer allowing applied sciences for personalisation and version at the world-wide-web. The e-book includes the papers awarded in the course of the workshop. shows of the papers can be found on-line at www.hci.gr.

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In SIAM conference on Data Mining, pp. 531–547, Arlington, VA, 2002. 31. O. Nasraoui, R. Krishnapuram, H. Frigui, and Joshi A. Extracting web user profiles using relational competitive fuzzy clustering. International Journal of Artificial Intelligence Tools, 9(4):509–526, 2000. 32. O. Nasraoui, R. Krishnapuram, and A. Joshi. Mining web access logs using a relational clustering algorithm based on a robust estimator. In 8th International World Wide Web Conference, pp. 40–41, Toronto, Canada, 1999. 33.

Abidi, and V. Shah. Knowledge discovery from users web-page navigation. In Proceedings of workshop on research issues in Data engineering, Birmingham, England, 1997. 42. M. C. Faulstich. Wum: A web utilization miner. In Proceedings of EDBT workshop WebDB98, Valencia, Spain, 1999. 43. J. Srivastava, R. Cooley, M. N. Tan. Web usage mining: Discovery and applications of usage patterns from web data. SIGKDD Explorations, 1(2):1–12, Jan 2000. A Multi-Layered and Multi-Faceted Framework 35 44. L. Terveen, W.

For example, it is possible to discover dynamic trends within Web profile communities based on intuitive rules that relate the angle between the velocities of the synopsis nodes in a node community: Expansion, Focusing, and Drift. Each dynamic behavior can be detected based on the following simple rules, which are intuitive as can be verified in Fig. 3: Fig. 3. Dynamic Trends within Synopsis Communities: Drifting (left picture), Expansion (middle), and Shrinking (right) clear circles = synopsis nodes, darker circle = centroid of community, arrows = velocities 30 O.

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Adaptive and Personalized Semantic Web by Christos Makris, Yannis Panagis (auth.), Spiros Sirmakessis Dr. (eds.)

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