A data mining framework for building a Web-page recommender system

Choochart Haruechaiyasak, Mei Ling Shyu, Shu Ching Chen

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

9 Scopus citations

Abstract

In this paper, we propose a new framework based on data mining algorithms for building a Web-page recommender system. A recommender system is an intermediary program (or an agent) with a user interface that automatically and intelligently generates a list of information which suits an individual's needs. Two information filtering methods for providing the recommended information are considered: (1) by analyzing the information content, i.e., content-based filtering, and (2) by referencing other user access behaviors, i.e., collaborative filtering. By using the data mining algorithms, the information filtering processes can be performed prior to the actual recommending process. As a result, the system response time could be improved and thus, making the framework scalable.

Original languageEnglish (US)
Title of host publicationProceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004
EditorsA.M. Memon, N. Zhao
Pages357-362
Number of pages6
StatePublished - Dec 1 2004
EventProceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004 - Las Vegas, NV, United States
Duration: Nov 8 2004Nov 10 2004

Publication series

NameProceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004

Other

OtherProceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004
CountryUnited States
CityLas Vegas, NV
Period11/8/0411/10/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Haruechaiyasak, C., Shyu, M. L., & Chen, S. C. (2004). A data mining framework for building a Web-page recommender system. In A. M. Memon, & N. Zhao (Eds.), Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004 (pp. 357-362). (Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004).