Web service recommendation using PCC based collaborative filtering

With the increasing amount of web services on the Internet, web service selection and recommendation are becoming more and more important. This paper finds the list of optimal web service to target user by his history. For finding list of optimal web services we use two methodologies i.e. Pearson Correlation Coefficient based Collaborative Filtering (PCC) and Normal Recovery Collaborative Filtering methodology. PCC and NRCF uses similarity measure algorithm for web service similarity computation. Compared with existing methods, the proposed system has new Hybrid clustering techniques which improve PCC prediction accuracy and it is only based on PCC similarity measure. To evaluate the web service recommendation system performance, we conduct experiments on PCC with new clustering technique. The experimental results show comparison of PCC and NRCF.