A SEMANTIC-BASED SERVICE DISCOVERY FRAMEWORK FOR COLLABORATIVE ENVIRONMENTS

In recent years, service-oriented and ubiquitous technologies have experienced impressive development. As these services grow rapidly both in scale and type, effective and accurate service discovery methods play an increasingly important role in the search and selection of services that match consumer requirements and preferences. In order to discover the optimum service and enhance the effectiveness of discovered results, a semantic-based service discovery framework, consisting of user model, context model, service model and a service discovery process, was presented in this study. Then the personalized service ontology was introduced to adjust the service search range adaptively on the basis of the service ontology structure and user information. Furthermore, a semantic-based service discovery method was designed in the proposed framework, which enabled names, attributes and relations of services to be more accurately matched and mapped with user preferences. Finally, to evaluate the effectiveness and accuracy of this method, the simulation analysis was conducted based on service ontology, in which information on 102 separate services and 10 scenarios were extracted from actual data. The simulation results show that compared with the keywords-based method, the proposed semantic-based method shows an increase in recall rate, precision and F-measure. The simulation results also reveal that the proposed method improves service discovery efficiency and performs well in accuracy. Therefore, collaborative environments considered in service discovery can provide useful and effective guidance to study the service recommendation.