Concept Learning of Text Documents
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Using WI Technologies to Develop Intelligent Portals - Research Activities at the WIC Japan Center -
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Mining Ontology for Automatically Acquiring Web User Information Needs
IEEE Transactions on Knowledge and Data Engineering
Automatically Acquiring Training Sets for Web Information Gathering
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Utilizing Search Intent in Topic Ontology-Based User Profile for Web Mining
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
A knowledge retrieval model using ontology mining and user profiling
Integrated Computer-Aided Engineering
Construction of Ontology-Based User Model for Web Personalization
UM '07 Proceedings of the 11th international conference on User Modeling
Relevence Assessment of Topic Ontology
Proceedings of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006
Depth First Rule Generation for Text Categorization
Proceedings of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006
Concept-Based, Personalized Web Information Gathering: A Survey
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Ontology based web mining for information gathering
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
Extracting significant Website Key Objects: A Semantic Web mining approach
Engineering Applications of Artificial Intelligence
Web data mining and reasoning model
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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Web mining is used to search the right information from the Web to meet user information needs. Acquiring correct user profiles is difficult, since users may be unsure of their interests and may not wish to invest a great deal of effort in creating such a profile. Our aim is to present a foundation for representations of user profiles on ontology for designing efficient Web mining models. In this paper, we assume the user concept can be constructed from some primary ones; hence, we use "part-of" relation to describe the relationship between classes. We also present set-valued relevance functions on such ontology to unravel the relationships between facts and the existing classes. A numerical interpretation is also presented for the set-valued relation functions.