Mining contextual knowledge for context-aware recommender systems

Zhang, Wenping and Lau, Raymond and Tao, Xiaohui ORCID: https://orcid.org/0000-0002-0020-077X (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. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Faculty/School / Institute/Centre: Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Faculty/School / Institute/Centre: Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
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 (2008): 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
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified
46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460208 Natural language processing
49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490302 Numerical analysis
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: https://doi.org/10.1109/ICEBE.2012.65
URI: http://eprints.usq.edu.au/id/eprint/23125

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