Web site improvements based on representative pages identification

Authors:
Sebastían A. Ríos;Juan D. Velásquez;Hiroshi Yasuda;Terumasa Aoki
Affiliations:
Research Center for Advanced Science and Technology, University of Tokyo;Department of Industrial Engineering, University of Chile;Research Center for Advanced Science and Technology, University of Tokyo;Research Center for Advanced Science and Technology, University of Tokyo
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

Citing 5
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Abstract

Many researchers have successfully shown that web content mining technics and web usage mining techniques can help to find out important patterns on the content and browsing behavior in a site. However, still it is an open problem how to reach a good interpretation of the cluster results after the mining process. We propose a technique called Reverse Clustering Analysis (RCA) applied to a Self Organizing Feature Map in order to identify the most representative Web Pages of the Site. Then use this information to perform enhancements in the site. Our mining process is based on the combination of WCM and WUM to find out the content that is most interesting for the visitors. We successfully test our proposal in a real web site.