An ontology-based framework for knowledge retrieval

Tao, Xiaohui and Li, Yuefeng and Zhong, Ning and Nayak, Richi (2008) An ontology-based framework for knowledge retrieval. In: 2008 IEEE/WIC/ACM International Conference on Web Intelligence, 9-12 Dec 2008, Sydney, Australia.

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Abstract

Retrieving accurate information from the Web is a great challenge to users. The existing information retrieval systems are mostly term-based and thus need to be enhanced toward knowledge-based. User information needs need to be better captured in order to deliver personalized search results. In this paper, an ontology-based framework is proposed for capturing user information needs using a world knowledge base and the user's local instance repository. The framework aims to discover a user's background knowledge for knowledge retrieval. The evaluation result is encouraging, in which the proposed model achieved the same performance as a manual user model.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted Version deposited in accordance with the copyright policy of the publisher.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 01 Oct 2014 06:19
Last Modified: 26 Aug 2016 06:02
Uncontrolled Keywords: background knowledge; evaluation results; knowledge retrievals; ontology-based; personalized searches; user information needs; user models; world knowledge
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080603 Conceptual Modelling
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0807 Library and Information Studies > 080704 Information Retrieval and Web Search
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1109/WIIAT.2008.226
URI: http://eprints.usq.edu.au/id/eprint/20189

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