The growing number of web services puts forward higher requirements for searching desired web services and clustering Web services can greatly enhance the discovery of Web service.However

the existing clustering approaches are only for a single type of service documents

and they are lacking of considering the domain characteristic and the tags information of services.To solve these problems

the proposed approach constructs the feature vectors of Web service contents by using ontology empowered SVM and domain oriented feature dimension reduction technology.Then a tag aided service clustering model called T-LDA is proposed to construct the hidden topic representations of Web service and general topical information which has less discriminative power is normalized.Finally all methods mentioned above are combined to form the domain oriented and tag aided Web service clustering (DTWSC).Experimental results show that the proposed approach can improve the effect of clustering.Compared with the approaches of LDA and K-means

the proposed approach achieves better performance of the purity

entropy and F-measure.