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ABSTRACT

Domain ontology has been used in many Semantic Web applications. However, few applications explore the use of ontology for personalized services. This paper proposes an ontology based user model consisting of both concepts and semantic relations to represent users' interests. Specifically, we adopt a statistical approach to learning a semantic-based user ontology model from domain ontology and a spreading activation procedure for inferencing in the user ontology model. We apply the methods of learning and exploiting user ontology to a semantic search engine for finding academic publications. Our experimental results support the efficacy of user ontology and spreading activation theory (SAT) for providing personalized semantic services.

REFERENCES

• 1: Anderson, R. J. A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior 22 (1983), 261--295.
• 2: R. Guha , Rob McCool , Eric Miller, Semantic search, Proceedings of the 12th international conference on World Wide Web, May 20-24, 2003, Budapest, Hungary [doi>10.1145/775152.775250]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Performance

Keywords:
spreading-activation theory, user ontology