Combining uncorrelated similarity measures for service discovery

  • Authors:

  • Fernando Sánchez-Vilas;Manuel Lama;Juan C. Vidal;Eduardo Sánchez

  • Affiliations:

  • Departamento de Electrónica e Computación, Universidade de Santiago de Compostela, Santiago de Compostela, Spain;Departamento de Electrónica e Computación, Universidade de Santiago de Compostela, Santiago de Compostela, Spain;Departamento de Electrónica e Computación, Universidade de Santiago de Compostela, Santiago de Compostela, Spain;Departamento de Electrónica e Computación, Universidade de Santiago de Compostela, Santiago de Compostela, Spain

  • Venue:
  • RED'10 Proceedings of the Third international conference on Resource Discovery
  • Year:
  • 2010

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Abstract

In this paper we present an OWL-S service matchmaker that combines uncorrelated similarity measures for obtaining the services that match a given request. These similarity measures are obtained comparing four of the elements presented in the OWL-S Service Profile: name, description, and the collection of both inputs and outputs of a service and a request. For each of these elements a number of similarity measures can be applied and combined in several formulas in order to obtain a similarity value. Once these measures are calculated a neural network is trained to combine the uncorrelated similarity measures with the purpose of obtaining a degree of the suitability of a given service for a particular request. This matchmaker has been validated in the OWL-S TC v3 service library.