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A multi-level approach for selecting and recommending semantic web services

Over the past few years, the number of web services has grown rapidly and the task of selecting the relevant service that satisfy the user request becomes more and more difficult. Most proposed approaches for web services selection focuses on functional characteristics of services, and those who adopt the recommender system (RS) techniques to take into account the no-functional requirements give more importance to the user side. Thus, there is a need of an approach that combines the two above perspectives by focusing on the user side (explicit and implicit requirements) and the service side (services capabilities). In this paper we propose a multi-level approach to select and recommend Semantic web services, the first level assumes the semantic functional services selection. The second level aims at filtering and ranking the selected services based on quality of services criteria (i.e. no-functional requirements) while the third level is a collaborative filtering RS which aims to enhance and increase the accuracy of the selection process. The experiment was performed using a test dataset and proves the effectiveness of our approach.