Rough sets based reasoning and pattern mining for a two-stage information filtering system

Xujuan Zhou, Yuefeng Li, Peter Bruza, Yue Xu, Raymond Y. K. Lau

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed two-stage filtering model significantly outperforms other types of "two-stage" information filtering models.
Original languageEnglish
Title of host publicationProceedings of the 19th ACM international conference on Information and knowledge management
Place of PublicationNew York, N.Y.
PublisherACM
Pages1429-1432
Number of pages4
ISBN (Print)9781450300995
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventCIKM '10 : International Conference on Information and Knowledge Management (19th : 2010) - Toronto, ON, Canada
Duration: 26 Oct 201030 Oct 2010

Conference

ConferenceCIKM '10 : International Conference on Information and Knowledge Management (19th : 2010)
CityToronto, ON, Canada
Period26/10/1030/10/10

Keywords

  • decision
  • experimentation
  • theory

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