An ant-inspired approach for semantic web service clustering

This paper presents a method inspired by ants behavior for creating clusters of semantic Web services. The clustering method groups services according to their semantic similarity. Services are grouped in the same cluster if they provide similar functionality and their input and output parameters are annotated with similar ontology concepts. We propose a matching method which evaluates the semantic similarity level between two service descriptions. The ant-based clustering method was tested and validated on the set of semantic Web services included in the SAWSDL-TC benchmark collection.