Capturing evolving patterns for ontology-based web mining
Li, Yuefeng & Zhong, Ning (2004) Capturing evolving patterns for ontology-based web mining. In Zhong, N., Tirri, H., & Yao, Y. (Eds.) IEEE/WIC/ACM International Joint Conference on Web Intelligence (WI) and Intelligent Agent Technology (IAT), 20-24 Sept. 2004, Beijing, China.
An ontology-based Web mining model tends to extract an ontology from user feedback and use it to search the right data from the Web to answer what users want. It is indubitable that we can obtain numerous discovered patterns using a Web mining model. However, some discovered patterns might include uncertainties when we extract them. Also user profiles are changeable. Therefore, the difficult issue is how to use and maintain the discovered patterns. This paper presents a theoretical framework for this issue, which consists of automatic ontology extraction, reasoning on the ontology and capturing evolving patterns. The experimental results show that all objectives we expect for the theoretical framework are achievable.
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|Item Type:||Conference Paper|
|Keywords:||Ontology, based Web mining, data mining, data reasoning, ontology learning, pattern evolution|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2004 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||19 Apr 2007|
|Last Modified:||29 Feb 2012 13:09|
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