Mining contextual knowledge for context-aware recommender systems

Zhang, Wenping and Lau, Raymond and Tao, Xiaohui (2012) Mining contextual knowledge for context-aware recommender systems. In: 9th IEEE International Conference on E-Business Engineering (ICEBE 2012), 9-11 Sep 2012, Hangzhou, China.

Abstract

With the rapid growth of the number of electronic transactions conducted over the Internet, recommender systems have been proposed to provide consumers with personalized product recommendations. A hybrid symbolic and quantitative approach for recommender agent systems is promising because it can improve the recommender agents' prediction effectiveness, learning autonomy, and explanatory power. However, recommender agents must be empowered with sufficient domain-specific knowledge so as to reason about specific recommendation contexts to improve their prediction accuracy. This paper illustrates a novel text mining method which is applied to automatically extract domain-specific knowledge for context-aware recommendations. According to our preliminary experiments, recommender agents empowered by the text mining mechanism outperform the agents without text mining capabilities. To our best knowledge, this is the first study of integrating text mining method into a symbolic logical framework for the development of recommender agents.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 IEEE. Permanent restricted access to published version due to publisher copyright policy.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 09 Apr 2013 00:32
Last Modified: 23 Feb 2015 01:37
Uncontrolled Keywords: belief revision; intelligent agents; recommender systems; text mining
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 > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010301 Numerical Analysis
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1109/ICEBE.2012.65
URI: http://eprints.usq.edu.au/id/eprint/23125

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