Tao, Xiaohui and Li, Yuefeng and Zhong, Ning (2010) A knowledge-based model using ontologies for personalized web information gathering. Web Intelligence and Agent Systems: an International Journal, 8 (3). pp. 235-254. ISSN 1570-1263
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Identification Number or DOI: doi: 10.3233/WIA-2010-0189
Nowadays, how to gather useful and meaningful information from the Web has become challenging to all users because of the explosion in the amount of Web information. However, the mainstream of Web information gathering techniques has many drawbacks, as they are mostly keyword-based. It is argued that the performance of Web information gathering systems can be significantly improved if user background knowledge is discovered and a knowledge-based methodology is used. In this paper, a knowledge-based model is proposed for Web information gathering. The model uses a world knowledge base and user local instance repositories for user profile acquisition and the capture of user information needs. The knowledge-based model was successfully evaluated by comparing a manually implemented user concept model. The proposed knowledge-based model contributes to better designs of knowledge-based and personalized Web information gathering systems.
|Item Type:||Article (Commonwealth Reporting Category C)|
|Additional Information:||Permanent restricted access to published version due to publisher copyright policy.|
|Uncontrolled Keywords:||knowledge-based information gathering; local instance repository; ontology; user background knowledge; user information needs; world knowledge base|
|Fields of Research (FOR2008):||08 Information and Computing Sciences > 0806 Information Systems > 080602 Computer-Human Interaction|
08 Information and Computing Sciences > 0805 Distributed Computing > 080505 Web Technologies (excl. Web Search)
08 Information and Computing Sciences > 0807 Library and Information Studies > 080704 Information Retrieval and Web Search
|Socio-Economic Objective (SEO2008):||E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences|
|Deposited On:||17 May 2011 18:33|
|Last Modified:||31 Jul 2012 11:53|
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