Publication Type

Journal Article

Version

publishedVersion

Publication Date

7-2009

Abstract

User modeling is aimed at capturing the users’ interests in a working domain, which forms the basis of providing personalized information services. In this paper, we present an ontology based user model, called user ontology, for providing personalized information service in the Semantic Web. Different from the existing approaches that only use concepts and taxonomic relations for user modeling, the proposed user ontology model utilizes concepts, taxonomic relations, and non-taxonomic relations in a given domain ontology to capture the users’ interests. As a customized view of the domain ontology, a user ontology provides a richer and more precise representation of the user’s interests in the target domain. Specifically, we present a set of statistical methods to learn a user ontology from a given domain ontology and a spreading activation procedure for inferencing in the user ontology. The proposed user ontology model with the spreading activation based inferencing procedure has been incorporated into a semantic search engine, called OntoSearch, to provide personalized document retrieval services. The experimental results, based on the ACM digital library and the Google Directory, support the efficacy of the user ontology approach to providing personalized information services.

Keywords

Semantic Web, User ontology, Domain ontology, Personalization, Spreading activation theory

Discipline

Computer Engineering | Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Information Sciences

Volume

179

Issue

6

First Page

2794

Last Page

2808

ISSN

0020-0255

Identifier

10.1016/j.ins.2009.04.005

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.ins.2009.04.005

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