Mining Ontology for Automatically Acquiring Web User Information Needs
IEEE Transactions on Knowledge and Data Engineering
Mining world knowledge for analysis of search engine content
Web Intelligence and Agent Systems
A knowledge retrieval model using ontology mining and user profiling
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Relevence Assessment of Topic Ontology
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KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Mining rough association from text documents for web information gathering
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Ontology based web mining for information gathering
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
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AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Mining rough association from text documents
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
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AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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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.