A knowledge retrieval model using ontology mining and user profiling

Article type: Research Article

Authors: Tao, Xiaohui^{; *} | Li, Yuefeng | Nayak, Richi

Affiliations: Faculty of Information Technology, Queensland University of Technology, Brisbane, Australia

Correspondence: [*] Corresponding author. E-mail: x.tao@qut.edu.au.

Abstract: Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated the user need for efficient mechanisms for information and knowledge location, selection and retrieval. Much research in the area of semantic web is already underway, adopting information retrieval tools and techniques. However, much work is required to address knowledge retrieval; for instance, users' information needs could be better interpreted, leading to accurate information retrieval. In this paper, a novel computational model is proposed for solving retrieval problems by constructing and mining a personalized ontology based on world knowledge and a user's Local Instance Repository. The proposed model is evaluated by applying to a Web information gathering system, and the result is promising.

DOI: 10.3233/ICA-2008-15404

Journal: Integrated Computer-Aided Engineering, vol. 15, no. 4, pp. 313-329, 2008