Pattern mining for a two-stage information filtering system

Zhou, Xujuan and Li, Yuefeng and Bruza, Peter and Xu, Yue and Lau, Raymond Y. K. (2011) Pattern mining for a two-stage information filtering system. Lecture Notes in Computer Science, 6634 (1). pp. 363-374. ISSN 0302-9743

Abstract

As information available over computer networks is growing exponentially, searching for useful information becomes increasingly more difficult. Accordingly, developing an effective information filtering mechanism is becoming very important to alleviate the problem of information overload. Information filtering systems often employ user profiles to represent users’ information needs so as to determine the relevance of documents from an incoming data stream. 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 both the term-based and pattern-based information filtering models.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty / Department / School: Historic - Faculty of Business and Law - School of Information Systems
Date Deposited: 15 Sep 2017 03:17
Last Modified: 01 Nov 2017 02:25
Uncontrolled Keywords: pattern mining, information filtering, user profile, threshold
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: dou:10.1007/978-3-642-20841-6_30
URI: http://eprints.usq.edu.au/id/eprint/30980

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