Service of Searching and Ranking in a Semantic-Based Expert Information System

Selecting professional and authoritative experts to evaluate projects is an essential process in order to assure the quality of projects. In this paper, we present a semantic-based expert information system, which search for expert information based on semantic and knowledge reasoning, and rank the search results according to the scientific capability of experts. We design software architecture for semantic-based information service system (Esoogle). Expert information ontology is defined to store the information of experts, and reasoning rules are defined for semantic-based reasoning. Assessment model based on TOPSIS is built to estimate the scientific capability for ranking. Applications show Esoogle improves the recall and precision of semantic-based searching service compared to the traditional systems and ranking service is helpful for the users to select suitable experts quickly.