Ontology mining for personalized web information gathering

Tao, Xiaohui and Li, Yuefeng and Zhong, Ning and Nayak, Richi (2007) Ontology mining for personalized web information gathering. In: 2007 IEEE/WIC/ACM International Conference on Web Intelligence, 2-5 Nov 2007, Fremont, CA. United States.

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It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of 'kind-of', 'part-of', and 'related-to' and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.

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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: 26 Aug 2016 06:02
Last Modified: 26 Aug 2016 06:02
Uncontrolled Keywords: web searching; ontology; information theory; knowledge based systems; semantics
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/WI.2007.88
URI: http://eprints.usq.edu.au/id/eprint/20192

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