Title: Expert selection service system by fuzzy ontology modelling

Authors: Liu Yang; Zhi-gang Hu; Jun Long

Addresses: School of Software, Central South University, Changsha 410075, China ' School of Software, Central South University, Changsha 410075, China ' School of Information Science and Engineering, Central South University, Changsha 410075, China

Abstract: Classical ontology is insufficient for handling vague and imprecise information. To deal with this problem, a four-layered structure of fuzzy domain ontology based on fuzzy logic theory is designed to extend classical domain ontology in this paper. Fuzzy concepts, fuzzy properties and fuzzy memberships are defined in the fuzzy domain ontology to describe knowledge with uncertainty based on semantics. Applying this four-layered extended structure of fuzzy domain ontology, expert fuzzy ontology in the domain of science and technology evaluation is developed, and expert selection algorithm based on fuzzy ontology is designed to realise expert selection service according to selection requirements with vague and imprecise semantics. The practical application results show that semantic expert selection service can not only work more efficiently and accurately for expert selection than keyword-based expert selection service and classical ontology-based expert selection service, but also provide decision support for it.

Keywords: fuzzy ontology; science and technology evaluation; semantic retrieval; expert selection; ontology modelling; fuzzy logic; uncertainty; science experts; technology experts.

DOI: 10.1504/IJCSE.2016.076215

International Journal of Computational Science and Engineering, 2016 Vol.12 No.2/3, pp.124 - 132

Received: 12 Feb 2013
Accepted: 02 Jun 2013
Published online: 30 Apr 2016 *

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