A two-stage decision model for information filtering

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

12 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)706-716
Journal / PublicationDecision Support Systems
Volume52
Issue number3
Publication statusPublished - Feb 2012

Abstract

Information mismatch and overload are two fundamental issues influencing the effectiveness of information filtering systems. Even though both term-based and pattern-based approaches have been proposed to address the issues, neither of these approaches alone can provide a satisfactory decision for determining the relevant information. This paper presents a novel two-stage decision model for solving the issues. The first stage is a novel rough analysis model to address the overload problem. The second stage is a pattern taxonomy mining model to address the mismatch problem. The experimental results on RCV1 and TREC filtering topics show that the proposed model significantly outperforms the state-of-the-art filtering systems. © 2011 Elsevier B.V. All rights reserved.

Research Area(s)

  • Decision models, Information filtering, Pattern mining, Text classification, User profiles

Citation Format(s)

A two-stage decision model for information filtering. / Li, Yuefeng; Zhou, Xujuan; Bruza, Peter; Xu, Yue; Lau, Raymond Y.K.

In: Decision Support Systems, Vol. 52, No. 3, 02.2012, p. 706-716.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review