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A web personalization system based on web usage mining techniques
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Source International World Wide Web Conference archive
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters table of contents
New York, NY, USA
POSTER SESSION: Posters table of contents
Pages: 288 - 289  
Year of Publication: 2004
ISBN:1-58113-912-8
Authors
Massimiliano Albanese  Università di Napoli Federico II, Napoli, Italy
Antonio Picariello  Università di Napoli Federico II, Napoli, Italy
Carlo Sansone  Università di Napoli Federico II, Napoli, Italy
Lucio Sansone  Università di Napoli Federico II, Napoli, Italy
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

In the past few years, web usage mining techniques have grown rapidly together with the explosive growth of the web, both in the research and commercial areas. In this work we present a Web mining strategy for Web personalization based on a novel pattern recognition strategy which analyzes and classifies both static and dynamic features. The results of experiments on the data from a large commercial web site are presented to show the effectiveness of the proposed system.


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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C. De Stefano, C. Sansone, and M. Vento. Evaluating competitive learning strategies for handwritten character recognition. In IEEE Int. Conf. on Systems, Man and Cybernetics Proceedings, pages 759--764, Oct. 1994.
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F. Zhang and H. Chang. Research and development in web usage mining system--key issues and proposed solutions: a survey. In First IEEE Int. Conf. on Machine Learning and Cybernetics Proceedings, pages 986--990, Nov. 2002.


Collaborative Colleagues:
Massimiliano Albanese: colleagues
Antonio Picariello: colleagues
Carlo Sansone: colleagues
Lucio Sansone: colleagues