Abstract:The existing clustering approaches are lacking of researching on clustering Web services whose descriptions are semantic sparse.Therefore

a new approach was proposed to makes an attempt to solve the problem of clustering sematic sparse Web service by applying transfer learning method in the domain of Web service clustering.A dual PLSA model was introduced to integrate knowledge of target domain and auxiliary domain which can transfer knowledge using a unsupervised mode to facilitate the process of semantic sparse Web service clustering.Experimental results showed that the proposed method can improve the performance of semantic sparse Web service clustering.Compared with the approaches of K-means

Agglomerative and PLSA

the proposed approach achieves better performance of the purity and the entropy.