An IP Multimedia Subsystem Service Discovery and Exposure Approach Based on Opinion Mining by Exploiting Twitter Trending Topics

Abstract

Being one of the most solicited content (opinions) sharing platforms, Twitter is a granary of information serving as a base for our service discovery/exposure approach proposed in this paper. The growth of data caused by the internet growth has led to the birth of a growing number of services, making the task difficult for telecommunication operators in competition. In this paper, we propose a dual service discovery/exposure approach to reduce the gap between offered services and subscribers’ needs in an IMS context. This approach is based on opinion mining related to Twitter trending topics in order to estimate the sensitivity of the target user to a service or another. Compared to both the classic approach and the collaborative service discovery/exposure approach, our results show an improvement in the accuracy and error of the service targeting at the target user’s starting phase on the operator’s network.