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

Zhou, Xujuan, Li, Yuefeng, Bruza, Peter D., Xu, Yue, & Lau, Raymond Y.K. (2010) Rough sets based reasoning and pattern mining for a two-stage information filtering system. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management, ACM, Fairmont Royal York, Toronto, pp. 1429-1432.

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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 experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

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ID Code: 42071
Item Type: Conference Paper
Keywords: filtering model , term-based, pattern- based, rough analysis
DOI: 10.1145/1871437.1871639
ISBN: 9781450300995
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2010 ACM
Deposited On: 22 Jun 2011 13:09
Last Modified: 01 Mar 2012 00:29

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