A Two-stage information filtering based on rough decision rule and pattern mining
Zhou, Xujuan, Li, Yuefeng, Bruza, Peter, Xu, Yue, & Lau, Raymond (2010) A Two-stage information filtering based on rough decision rule and pattern mining. Journal of Emerging Technologies in Web Intelligence, 2(4), pp. 326-332.
Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. 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 twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.
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|Item Type:||Journal Article|
|Keywords:||Information Filtering, User Profiles, Rough Set Theory, Pattern Mining|
|Divisions:||Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > Information Systems
|Copyright Owner:||Copyright 2010 Academy Publisher|
|Deposited On:||04 Jan 2011 00:50|
|Last Modified:||22 Jun 2011 14:07|
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