Enhanced User Context-Aware Reputation Measurement of Multimedia Service

Abstract

Reputation plays an important role for users in choosing or paying for multimedia applications or services. Some efficient multimedia reputation-measurement approaches have been proposed to achieve accurate reputation measurement based on feedback ratings that users give to a multimedia service after invoking. However, the implementation of these approaches suffers from the problems of wide abuse and low utilization of user context. In this article, we study the relationship between user context and feedback ratings according to which one user often gives different feedback ratings to the same multimedia service in different user contexts. We further propose an enhanced user context-aware reputation-measurement approach for multimedia services that is accurate in two senses: (1) Each multimedia service has three reputation values with three different user context levels when its feedback ratings are sufficient and (2) the reputation of a multimedia service with different user context levels is found using user context sensitivity and user similarity when its feedback ratings are limited or not available. Experimental results based on a real-world dataset show that our approach outperforms other approaches in terms of accuracy.