Research And Design On Web Service Reputation Measurement Based On User’s Context

Reputation is used to describe the credibility and reliability of QoS claimed by service provider. Its measurement is based on the feedback ratings that users give to the service after invoking. Feedback ratings reflect users’subjective feeling and objective effect according to the acquired QoS. Accurate reputation value is very important for users to choose services. Therefore, Web service reputation measurement has become a hot research topic in the field of service computing.Although many existing approaches can effectively improve the accuracy of Web service reputation measurement, they generally ignore the impact of user’s context on reputation measurement. For this purpose, we conduct deep research on the impact of user’s context and how to weaken the impact. We preprocess the feedback ratings by clustering user’s context and weakening its impact on feedback ratings. For different application scenarios, this paper proposes two approaches of Web service reputation measurement based on user’s context:1) Aiming at the problem that different user’s context may affect user’s feedback ratings differently, this paper proposes Web service reputation measurement approach based on user’s context clustering. This approach firstly models, formalizes and normalizes user’s context. Then, it clusters user’s context in order to use a comprehensive quantitative value to represent the level of user’context. Finally, this approach uses feedback ratings with the same context to measure Web service reputation, so that we can get different reputation value with different user’s context level. Experiment results show that, in such scenery that user’s context largely affects user’s feedback rating, our approach can effectively improve the accuracy of reputation measurement.2) Aiming at the problem that the existing approaches only use feedback ratings with the same context, which leads to low utilization of feedback ratings, this paper proposes Web service reputation measurement approach based on user’s context sensitivity. This approach firstly proposes the concept of user’s context sensitivity and measure it for users. Then, according to the acquired user’s context sensitivity, it weakens the user’s context impact on users’feedback ratings, and transfers feedback ratings into a unified reference context level. Finally, this approach measures users’ similarities according to the weakened feedback ratings, and then gets the service reputation value. Experiment results show that, in such scenery that users frequently invoke some fixed services, our approach can effectively improve the accuracy of reputation measurement.