A personalised ontology ranking model based on analytic hierarchy process Online publication date: Fri, 30-Aug-2019
by Jianghua Li; Chen Qiu
International Journal of Computational Science and Engineering (IJCSE), Vol. 19, No. 4, 2019
Abstract: Ontology ranking is one of the important functions of ontology search engines, which ranks searched ontologies based on the ranking model applied. A good ranking method can help users acquire the exactly required ontology from a considerable amount of search results, efficiently. Existing approaches to rank ontologies take only a single aspect into consideration and ignore users' personalised demands, hence produce unsatisfactory result. It is believed that, the factors that influence ontology importance and the users' demands both need to be considered comprehensively in ontology ranking. A personalised ontology ranking model based on the hierarchical analysis approach is proposed in this paper. We build a hierarchically analytical model and apply analytic hierarchy process to quantify ranking indexes and assign weights to them. The experimental results show that the proposed method can rank ontologies effectively and meet users' personalised demands.
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