Humans, Semantic Services and Similarity: A User Study of Semantic Web Services Matching and Composition

Eran Toch, Iris Reinhartz-Berger, Dov Dori

Abstract


Inferring similarity between Web services is a fundamental construct for service matching and composition. However, there is little evidence of how humans perceive similarity between services, a crucial knowledge for designing usable and practical service matching and composition algorithms. In this study we have experimented with 127 users to define and evaluate a model for service similarity in the context of semantic Web services. Our findings show that humans take a complex and sophisticated approach towards service similarity, which is more fine-grained than suggested by theoretical models of service similarity, such as logic-based approaches. We define a similarity model, based on our empirical findings and prove that the similarity model, expressed by a distance metric, is complete and that it closely predicts humans' perceptions of service similarity. Finally, we describe an application of a Web service search engine that implements our model.

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