Discovery of Web Frequent Patterns and User Characteristics from Web Access Logs: A Framework for Dynamic Web Personalization

Authors:
Sumeet Dua;S. S. Iyengar;Eungchun Cho
Affiliations:
-;-;-
Venue:
ASSET '00 Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET'00)
Year:
2000

Citing 0
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Bibliography

Technology supporting business solutions
Avaliação comparativa de algoritmos de personalização para direcionamento de conteúdo

CLIHC '05 Proceedings of the 2005 Latin American conference on Human-computer interaction

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Abstract

An automatic discovery method that discovers frequent access routines for unique clients from web access log files is presented. Proposed algorithm develops novel techniques to extract the sets of all predictive access sequences from semi-structured web access logs. Important user access patterns are manifested through the frequent traversal paths, thus helping understand user surfing behaviors. The predictive access routines discovered by AllFreSeq are also useful for understanding and improving web-site domain tree.