Mining web data to create online navigation recommendations

Juan D. Velásquez, Alejandro Bassi, Hiroshi Yasuda, Terumasa Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

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 the significant 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.

Original languageEnglish
Title of host publicationProceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
EditorsR. Rastogi, K. Morik, M. Bramer, X. Wu
Pages551-554
Number of pages4
Publication statusPublished - 2004 Dec 1
Externally publishedYes
EventProceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 - Brighton, United Kingdom
Duration: 2004 Nov 12004 Nov 4

Other

OtherProceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
CountryUnited Kingdom
CityBrighton
Period04/11/104/11/4

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Velásquez, J. D., Bassi, A., Yasuda, H., & Aoki, T. (2004). Mining web data to create online navigation recommendations. In R. Rastogi, K. Morik, M. Bramer, & X. Wu (Eds.), Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 (pp. 551-554)