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SEWeP: using site semantics and a taxonomy to enhance the Web personalization process
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Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Washington, D.C.
SESSION: Research track table of contents
Pages: 99 - 108  
Year of Publication: 2003
ISBN:1-58113-737-0
Authors
M. Eirinaki  Athens University of Economics and Business, Patision 76, Athens, Greece
M. Vazirgiannis  Athens University of Economics and Business, Patision 76, Athens, Greece
I. Varlamis  Athens University of Economics and Business, Patision 76, Athens, Greece
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 14,   Downloads (12 Months): 125,   Citation Count: 12
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ABSTRACT

Web personalization is the process of customizing a Web site to the needs of each specific user or set of users, taking advantage of the knowledge acquired through the analysis of the user's navigational behavior. Integrating usage data with content, structure or user profile data enhances the results of the personalization process. In this paper, we present SEWeP, a system that makes use of both the usage logs and the semantics of a Web site's content in order to personalize it. Web content is semantically annotated using a conceptual hierarchy (taxonomy). We introduce C-logs, an extended form of Web usage logs that encapsulates knowledge derived from the link semantics. C-logs are used as input to the Web usage mining process, resulting in a broader yet semantically focused set of recommendations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  12

Collaborative Colleagues:
M. Eirinaki: colleagues
M. Vazirgiannis: colleagues
I. Varlamis: colleagues