| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 103 === In service-based systems (SBS), the quality of services (QoS) plays an important role for application development by helping select more suitable services, based on QoS values, for those specified inside a workflow. There are several QoS prediction approaches proposed. However, the prediction accuracy is low when there are lack of historical records in the application environment. In this thesis, we propose a method to construct a virtual platform based on Gaussian distribution with stability and performance, and design a referral-based QoS prediction method associated with the virtual platform to improve prediction accuracy. The experimental results indicate that our approach is better than others with higher prediction accuracy.
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