IMS Predictive Collaborative Service Discovery Approach

Abstract

The increasing number of services gives the telecommunication operators a great opportunity to fulfil the demand of their subscribers. Indeed, since various practically comparative services are promptly accessible, to offer a service that is relevant to the subscriber is at the centre of the operator's concerns. This is the case of IMS (IP Multimedia Subsystem), which is this platform that effectively allows access to a range of varied services regardless of the underlying access networks. By this way, to offer services fitting the needs of the subscriber within the IMS remains a challenging issue. The service discovery approach by exploiting only the information associated with the user's profile has poor performance when the usage history of the target subscriber is not provided. This restricts the relevance of the proposed service. Therefore, in addition to the information associated with the target subscriber's profile, we are interested in the information associated with the profiles of other subscribers similar to that of the target subscriber to improve the accuracy of the service targeting. In this paper we present a collaborative approach applied to service discovery that is based on taking into account the degree of satisfaction of the user. By the end we demonstrate through our results a clear improvement in service targeting accuracy.