Due to the diversity of Web users and their complex personal demands, Quality of Service (QoS) information released by some users is not completely reliable, which affects the accuracy of the evaluation on service quality. To address this problem, a service quality evaluation model based on Credible Recommendation (TR-SQE) was presented. In TR-SQE, recommendation trust for the user was defined as the degree of similarity between user's recommendation data and user group's accumulated recommendation data. QoS data released by the user whose recommendations trust was lower than threshold were shielded. By using such correctional QoS information as recommendation data of service quality, then the user, according to the degree of similarity with recommended preference, evaluated service quality. Analysis and simulation results demonstrate that evaluation results from TR-SQE are basically consistent with the real quality of service, which has smaller MAE compared with the contrast methods, and it is helpful to the user's service selection.

Concerning the present situation that Quality of Service (QoS) evaluation methods ignore the implicit service quality assessment and lead to inaccurate results, a service evaluation method that comprehensively considered explicit and implicit quality attributes was put forward. Explicit quality attributes were expressed in vector form, using service quality assessment model, after quantization, normalization, then evaluation values were calculated; and implicit quality attributes were expressed according to the evaluation on similar users' recommendation. The users' credibility and difference between old and new users were considered in the evaluation process. Finally the explicit and implicit quality evaluation was regarded as the QoS evaluation results. The experiments were performed in comparison with three algorithms by using one million Web Service QoS data. The simulation results show that the proposed method has certain feasibility and accuracy.