A Personalized Ontology Model for Web Information Gathering
Data(s) |
2011
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Resumo |
As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful. |
Formato |
application/pdf |
Identificador | |
Publicador |
IEEE |
Relação |
http://eprints.qut.edu.au/42924/1/42924.pdf DOI:10.1109/TKDE.2010.145 Tao, Daniel, Li, Yuefeng, & Zhong, Ning (2011) A Personalized Ontology Model for Web Information Gathering. IEEE Transactions on Knowledge & Data Engineering, 23(4), pp. 496-511. http://purl.org/au-research/grants/ARC/DP0988007 |
Fonte |
Faculty of Science and Technology; Information Systems |
Palavras-Chave | #080400 DATA FORMAT #080704 Information Retrieval and Web Search #Ontology, personalization, semantic relations, world knowledge, local instance repository, user profiles, web information gathering |
Tipo |
Journal Article |