Semantic Web Service Discovery Based on Text Clustering and Similarity of Concepts
Liu Yi-son · 2013
emantic Web Services need to match services in the registry in succession in the discovery of services,which wastes a lot of time on irrelevant services,and reduces efficiency of discovery.Thus,a new discovery method of semantic Web service based on text clustering and similarity of concepts was proposed which can be divided into two phases:in the first phase,services of identical category are clustered according to descriptive texts in the service source file when texts are expressed and processed by vector space modal(VSM)and a multiple hybrid clustering algorithm MHC was proposed in the second phase,functions and properties between services are matched and semantic similarity between concepts is calculated combined with factors such as depth,strength and inheritance of directed edge in the hierarchical tree of ontology concepts.Finally,the experimental result shows that the method proposed in the article improves the matching efficiency greatly based on accurate rate.