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Semantic Web Services pp 141–157Cite as

Self-Adaptive Semantic Matchmaking Using COV4SWS.KOM and LOG4SWS.KOM

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Abstract

This chapter presents the methodological and technical approach, as well as evaluation results, for two semantic matchmakers, COV4SWS.KOM and LOG4SWS.KOM. Both matchmakers operate on WSDL-based service description with SAWSDL annotations. COV4SWS.KOM applies similarity measures from the field of semantic relatedness, namely the metrics by Lin and Resnik. It automatically adapts to varying expressiveness of a service description on different abstraction levels through the utilization of an Ordinary Least Squares (OLS) estimator. LOG4SWS.KOM employs traditional subsumption reasoning, but maps the resulting discrete Degrees of Match (DoMs) to numerical equivalents to allow for the integration with additional similarity measures. As proof of concept, a path length-based measure is applied. The DoM mapping process may either be conducted manually or using an OLS estimator. Both matchmakers participated in the Semantic Service Selection (S3) Contest in 2010, providing very competitive evaluation results across all regarded performance metrics.

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Notes

  1. 1.

    The names of our matchmakers have historical roots: COV was traditionally based on the determination of the degree of coverage between semantic concepts; LOG refers to logic subsumption matching. The common name component 4SWS means “for Semantic Web Services”, KOM refers to the abbreviated name of our institute at Technische Universität Darmstadt.

  2. 2.

    As a matter of fact, both matchmakers are also applicable to service description formalisms that exhibit a structure similar to (SA)WSDL. An application of LOG4SWS.KOM to hRESTS with MicroWSMO annotations – service description formalisms for RESTful services – has been presented by Lampe et al. [12].

  3. 3.

    http://clarkparsia.com/pellet/

  4. 4.

    http://jwordnet.sourceforge.net/

  5. 5.

    http://www.jdom.org/

  6. 6.

    In fact, we utilize generic definitions of DoMs in LOG4SWS.KOM that slightly deviates from the ones introduced by Paolucci et al. [21]. However, this does not have any practical implications for the evaluated configurations. For additional details, please refer to our previous work [27].

  7. 7.

    Both test collections are available at http://projects.semwebcentral.org/projects/sawsdl-tc/

  8. 8.

    http://projects.semwebcentral.org/projects/sme2/

  9. 9.

    Using the mean average of each metric across the comparable Variants 1A–3B as a basis for comparison.

  10. 10.

    http://www.semwebcentral.org/projects/owls-tc/

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Authors and Affiliations

  1. Technische Universität Darmstadt, Darmstadt, Germany

    Ulrich Lampe & Stefan Schulte

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  1. Ulrich Lampe
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  2. Stefan Schulte
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Correspondence to Ulrich Lampe .

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Editors and Affiliations

  1. University of Miami, 1252 Memorial Drive, Ashe Building 325C, Coral Gables, 33124-4628, Florida, USA

    Brian Blake

  2. , Knowledge Media Institute - KMI, The Open University, Walton Hall, Milton Keynes, MK76AA, United Kingdom

    Liliana Cabral

  3. Fak. Mathematik und Informatik, Inst. Informatik, Universität Jena, Ernst-Abbe-Str. 2, Jena, 07743, Thüringen, Germany

    Birgitta König-Ries

  4. University of Jena, Jena, 07743, Germany

    Ulrich Küster

  5. SRI International, Ravenswood Ave. 333, MENLO PARK, 94025-3493, California, USA

    David Martin

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Lampe, U., Schulte, S. (2012). Self-Adaptive Semantic Matchmaking Using COV4SWS.KOM and LOG4SWS.KOM. In: Blake, B., Cabral, L., König-Ries, B., Küster, U., Martin, D. (eds) Semantic Web Services. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28735-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-28735-0_9

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