In this work we propose a two-step, context-based semantic approach to the problem of matching and ranking web services for possible service composition. We present an analysis of different methods for classifying Web services for possible composition and supply a context-based semantic matching method for ranking these possibilities. Semantic understanding of Web services may provide added value by identifying new possibilities for compositions of services. The semantic matching ranking approach is unique since it provides the Web service designer with an explicit numeric estimation of the extent to which a possible composition “makes sense. ” First, we analyze two common methods for text processing, TF/IDF and context analysis, and two types of service description, free text and WSDL. Second, we present a method for evaluating the proximity of services for possible compositions. Each Web service WSDL context descriptor is evaluated according to its proximity to other services ’ free text context descriptors. The methods were tested on a large repository of real-world Web services. The experimental results indicate that context analysis is more useful than TF/IDF. Furthermore, the method evaluating the proximity of the WSDL description to the textual description of other services provides high recall and precision results.

Abstract. Ontologies have become the de-facto modeling tool of choice, used in a variety of applications and prominently in the Semantic Web. Their design and maintenance, nevertheless, have been and still are a daunting task. As a result, ontologies quickly become underspecified. Therefore, if ontologies do not evolve, the semantic infrastructure of the information system can no longer support the changing needs of the organization. In this work we provide a model to semi-automatically support relationship evolution in an ontology using contexts. We propose to use (machine-generated) contexts as a mechanism for quantifying relationships among concepts. To do so we compare the contexts that are associated with the ontology constructs. On a conceptual level, we introduce an ontology verification model, a quantified model for automatically assessing the validity of relationships in an ontology. We motivate our work with examples from the field of eGovernment applications. To support our model with an empirical analysis, we provide a mapping of an ontology operator for defining relationships into context relationships, using real-world traces of RSS. 1