A web service recommendation algorithm based on BaisSVD

With the development of network technology and network services, the number of Web services will also be exploded, so the magnitude of Web services that can provide similar functions will gradually be increased. Quality of service (QoS) is widely used to describe and evaluate the non functional properties of Web services, and has been successfully applied to service recommendation. However, most of the current Web Service recommendations are still limited to traditional collaborative filtering, without considering the bias information of users and web services themselves. In this thesis, firstly, the author introduces the current situation of web services recommendation, then analyzes the existing problems and the characteristics of the data sets. Finally, the author applies the BiasSVD to predict QoS, and then recommends to users. By comparing the experimental results with the traditional collaborative filtering algorithm, the feasibility and superiority of the algorithm in Web services recommendation scenarios are obtained.