LOG4SWS.KOM: Self-Adapting Semantic Web Service Discovery for SAWSDL

In recent years, a number of approaches to semantic Web service matchmaking have been proposed. Most of these proposals are based on discrete and thus relatively coarse Degrees of Match (DoMs). However, different basic assumptions regarding the generalization and specialization of semantic concepts in ontologies and their subsequent rating in matchmaking exist. Hence, most matchmakers are only properly suitable if these assumptions are met. In this paper, we present an approach for mapping subsumption reasoning-based DoMs to a continuous scale. Instead of determining the numerical equivalents of the formerly discrete DoMs manually, these values are automatically derived using a linear regression model. This permits not only easy combination with other numerical similarity measures, but also allows to adapt matchmaking to different basic assumptions. These notions are implemented and tested in LOG4SWS.KOM-a matchmaker for SAWSDL that provides very good evaluation results with respect to Information Retrieval metrics such as precision and recall.