A Semantic-Based Approach for Context-Aware Service Discovery

The increasingly growing number of services available on the web, along with advances in information and communication technologies, has given rise to the development of new approaches for service discovery, devoted to retrieve services advertised by a service provider and satisfying users requests. Traditional service discovery attempts are devoted to enable a matching between advertised service names and the keywords of the user request. Some of these methods use also semantic approaches, however an improvement in terms of precision has been obtained with the adoption of a semantic-based approach, together with the use of contextual information. This research aims at facing the problem of discovering context-aware services by proposing a semantic similarity model for enabling the matching between advertisements and requests personalized according to the context information (such as user position, user preferences, available resources). The method proposed has been validated by performing a set of experiments for evaluating the recall and precision of the method.