The impact of the World Wide Web as a main source of information acquisition is increasing spectacularly. The existence of such abundance of information, in combination with the dynamic and assorted nature of the web, makes web site exploration a difficult process for the average user. To address the requirement of effective web navigation, web sites provide personalized recommendations to the end users. Most of the research efforts in web personalization correspond to the evolution of extensive research in web usage mining, i.e. the exploitation of the navigational patterns of the web site’s visitors. When a personalization system relies solely on usage-based results, however, valuable information conceptually related to what is finally recommended may be missed. Moreover, the structural properties of the web site are often disregarded.

1. Wu, Z., Palmer M. 1994. Verb Semantics and Lexical Selection. 32nd Annual Meetings of the Associations for Computational Linguistics.
2. Halkidi, M., Nguyen, B., Varlamis, I., Vazirgiannis, M., 2003. THESUS: Organizing Web Documents into Thematic Subsets using an Ontology, VLDB journal, 12(4): 320-332.
3. Varlamis, Vazirgiannis, M., Halkidi, M., Nguyen, B. 2004. THESUS, A Closer View on Web Content Management Enhanced with Link Semantics, in IEEE Trans. On Knowledge and Data Engineerign Journal (TKDE), 16(6):685-700,
4. Salton, G., Buckley C., 1998. Term-weighting approaches in automatic text retrieval, Information Processing and Management, 24:513-523.
5. Sugiyama, K., Hatano, K., Yoshikawa, M. 2004. Adaptive Web Search Based on User Profile Constructed without Any Effort from Users. In Proceedings of the 13th conference on World Wide Web.
6. Mobasher, B., Dai, H., Luo, et al. J. 2000. Discovery of Aggregate Usage Profiles for Web Personalization, in Proceedings of 2nd WEBKDD Workshop, Boston.
7. Brusilovsky, P., Kobsa, A. and Nejdl, W. Eds. 2007. The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, Vol. 4321, Springer Verlag, doi DOI= http://dx.doi.org/10.1007/978-3-540-72079-9.
8. Mobasher B., 2007. Data Mining for Web Personalization, The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, Vol. 4321, Springer Verlag, , DOI= http://dx.doi.org/10.1007/978-3-540-72079-9
9. Vishal Srivastava, Raj Gaurang Tiwari, Dr. R A Khan and Dr. Mohd. Husain. Article: Rummaging Around Workload Portrayal for Web Servers. International Journal of Computer Applications 14(2):1–5, January 2011.

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