A QoS Evaluation Algorithm for Web Service Ranking Based on Artificial Neural Network

As the number of Web service providers grows, redundancy becomes prevalent with many WS providers offering the same or similar services. Many models have been proposed to measure the QoS (quality of service). This paper is trying to address the Web service ranking problem based on QoS. A Web service relevancy ranking algorithm based on QoS parameters has been presented for the purpose of finding the best available Web service. In this ranking model, we try to find an automatic and objective way to recommend a Web service. The ranking process will reduce correlation degree and extract user preference. Attributes weight will be studied and adjusted through neural network. By this ways, the accuracy of the Web service ranking is improved.