关键词: Web服务, QoS预测, 协同过滤, 皮尔逊相关系数

Abstract: In the analysis of collaborative prediction approaches with Pearson Correlation Coefficient (PCC),the significant ratio relation was found between Web services and Quality of Service(QoS),while QoS prediction error  might caused by  ignoring the relationship of this ratio.To deal with the problem,a prediction approach considering the similarity ratio SRPre was proposed.Based on the historical QoS data,the combination of user-based approach and item-based approach was used.A minimum common call number threshold was introduced to reduce the calculation error of similarity,and a minimum similarity threshold was used to screen the similar neighbors.According to QoS average value ration of predicted object to similar neighbors,the similarity ratio was computed.The similarity ratio was added to the process of QoS collaborative prediction.The experimental results showed that the proposed approach was effective in improving the prediction accuracy.

Key words: Web service, quality of service prediction, collaborative filtering, Pearson correlation coefficient