Integration of information filtering and data mining process for Web information retrieval

Xujuan Zhou, Yuefeng Li, Peter Bruza, Yue Xu

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

Abstract

This paper examines a new approach to Web information retrieval, and proposes a new two stage scheme. The aim of the first stage is to quickly filter irrelevant information based on the user profiles. The proposed user profiles learning algorithm are very efficient and effective within a relevance feedback framework. The aim of the second stage is to apply data mining techniques to rationalize the data relevance on the reduced data set. Our experiments on RCV1 (Reuters Corpus Volume 1) data collection which is used by TREC in 2002 for filtering track show that more effective and efficient access Web information has been achieved by combining the strength of information filtering and data mining method.
Original languageEnglish
Title of host publicationADCS 2007
Subtitle of host publicationproceedings of the twelfth Australasian Document Computing Symposium
EditorsAmanda Spink, Andrew Turpin, Mingfang Wu
Place of PublicationMelbourne, Australia
PublisherRMIT University
Pages104-107
Number of pages4
ISBN (Print)9780646484372
Publication statusPublished - 2007
Externally publishedYes
EventAustralasian Document Computing Symposium (12th : 2007) - Melbourne
Duration: 10 Dec 200710 Dec 2007

Conference

ConferenceAustralasian Document Computing Symposium (12th : 2007)
CityMelbourne
Period10/12/0710/12/07

Keywords

  • Information filtering
  • User profiles
  • Data mining
  • Pattern taxonomic model

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