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A Personalized Ontology Mining for Web Information Retrieval
Abstract
Ontology is a formal description and specification of knowledge. Information systems are expected to be able to understand the semantic meaning of words and phrases, and be able to compare information items by concepts instead of keywords by using ontology models. In this project, a personalized ontology model is proposed, that learns ontological user profiles from both world knowledge base and user local instance repositories. Hence user background knowledge can be better discovered and represented while integrating global and local analysis within a hybrid model. This ontology model will be compared with several benchmark models and will be evaluated how it is successful in acquiring user required information. This project also extends the study on ontological mapping that will improve the performance of personalized user profiles.
Keywords
Ontology, Semantic Relations, Knowledge Engineering, Data Mining, User Profiles, Information Retrieval
References
Xiaohui Tao, Yuefeng Li, and Ning Zhong ,”A Personalized Ontology model for Web Information Gathering”, IEEE Transactions on Knowledge and Data Engineering, Vol.23,N0. 4, 2011.
S. Gauch, J. Chaffee, and A. Pretschner, “Ontology-Based Personalized Search and Browsing,” Web Intelligence and Agent Systems, vol. 1, nos. 3/4, pp. 219-234, 2003.
A. Doan, J. Madhavan, P. Domingos, and A. Halevy, “Learning to Map between Ontologies on the Semantic Web,” Proc. 11th Int’l Conf. World Wide Web (WWW ’02), pp. 662-673, 2002.
T. Tran, P. Cimiano, S. Rudolph, and R. Studer, “Ontology-Based Interpretation of Keywords for Semantic Search,” Proc. Sixth Int’l Semantic Web and Second Asian Semantic Web Conf. (ISWC ’07/ ASWC ’07), pp. 523-536, 2007.
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