Li, Yuefeng and Zhou, Xujuan and Bruza, Peter and Xu, Yue and Lau, Raymond Y.K. (2012) A two-stage decision model for information filtering. Decision Support Systems, 52 (3). pp. 706-716. ISSN 0167-9236
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.
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| Item Type: | Article (Commonwealth Reporting Category C) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Files associated with this item cannot be displayed due to copyright restrictions. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Business and Law - School of Management and Marketing (1 Jan 2011 - 30 June 2013) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Business and Law - School of Management and Marketing (1 Jan 2011 - 30 June 2013) |
| Date Deposited: | 05 Sep 2016 06:08 |
| Last Modified: | 13 Jan 2017 04:26 |
| Uncontrolled Keywords: | information filtering; Text classification; User profiles; Pattern mining; Decision models |
| Fields of Research : | 08 Information and Computing Sciences > 0806 Information Systems > 080605 Decision Support and Group Support Systems |
| Socio-Economic Objective: | E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences |
| Identification Number or DOI: | 10.1016/j.dss.2011.11.005 |
| URI: | http://eprints.usq.edu.au/id/eprint/29635 |
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