New PDF release: Adaptive and Personalized Semantic Web

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 that may tailor the internet event to a specific consumer or set of clients. to accomplish powerful personalization, firms needs to depend upon all on hand info, together with the utilization and click-stream facts (reflecting person behaviour), the location content material, the location constitution, area wisdom, in addition to consumer demographics and profiles. furthermore, effective and clever concepts are had to mine this knowledge for actionable wisdom, and to successfully use the found wisdom to reinforce the clients' internet event. the purpose of the foreign Workshop on Adaptive and custom-made Semantic net that was once held within the 16th ACM convention on Hypertext and Hypermedia (September 6-9, 2005, Salzburg, Austria) was once to collect researchers and practitioners within the fields of internet engineering, adaptive hypermedia, semantic net applied sciences, wisdom administration, details retrieval, consumer modelling, and different comparable disciplines which supply allowing applied sciences for customization and model at the world-wide-web. The e-book comprises the papers offered through the workshop. shows of the papers can be found on-line at

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C. Aggarwal, J. Han, J. Wang, and P. Yu. A framework for clustering evolving data streams. 2003. 3. C. Aggarwal, J. Han, J. S. Yu. A framework for clustering evolving data streams. In Proc. 2003 Int. Conf. on Very Large Data Bases (VLDB’03), Berlin, Germany, Sept 2003. 4. S. Babu and J. Widom. Continuous queries over data streams. In SIGMOD Record’01, pp. 109–120, 2001. 5. M. Balabanovic and Y. Shoham. Fab: Content-based, collaborative recommendation. Communications of the ACM, 40(3):67–72, 1997.

O. Nasraoui and R. Krishnapuram. One step evolutionary mining of context sensitive associations and web navigation patterns. 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.

SIGKDD Explorations, 1(2):1–12, Jan 2000. A Multi-Layered and Multi-Faceted Framework 35 44. L. Terveen, W. Hill, and B. Amento. Phoaks – a system for sharing recommendations. Comm. ACM, 40(3), 1997. 45. T. Yan, M. Jacobsen, H. Garcia-Molina, and U. Dayal. From user access patterns to dynamic hypertext linking. In Proceedings of the 5th International World Wide Web conference, Paris, France, 1996. 46. O. Zaiane and J. Han. Webml: Querying the world-wide web for resources and knowledge. In Workshop on Web Information and Data Management, 7th Intl.

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

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