Mining Web Data to Create Online Navigation Recommendations

Authors:
Juan D. Velasquez;Alejandro Bassi;Hiroshi Yasuda;Terumasa Aoki
Affiliations:
University of Tokyo, Japan/ University of Chile;University of Tokyo, Japan/ University of Chile;University of Tokyo, Japan;University of Tokyo, Japan
Venue:
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Year:
2004

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Abstract

A system to provide online navigation recommendation for web visitors is introduced. We call visitor the anonymous user, i.e., when only data about her/his browsing behavior (web logs) are available. We first apply clustering techniques over a large sample of web data. Next, from thesignificant patterns that are discovered, a set of rules about how to use them is created. Finally, comparing the current web visitor session with the patterns, online navigation recommendations are proposed using the mentioned rules. The system was tested using data from a real web site, showing its effectiveness.