Abstract (EN)

With the increasing number of services, the need to locate relevant services remains essential. To satisfy the query of a service requester, available service providers has first to be discovered. This task has been heavily investigated from both industrial and academic perspectives based essentially on registers. However, they completely ignore the contribution of the social dimension. When integrating social trust dimension to service discovery, this task will gain wider credibility and acceptance. If a service requester knows that discovered services are offered by trustworthy providers, he will be more confident. In this paper, we present a new discovery technique based on a social trust measure that ranks service providers belonging to the service requester’s multi-relation social network. The proposed measure is an aggregation of three measures: the social position, the social proximity and the social similarity. To compute these measures, we take into account both semantic and structural knowledge extracted from the multi-relation social network. Semantic information includes service requestor and provider profiles and their interactions. Structural information includes among other the position of service providers in the multi-relation social network graph.