Abstract—Service-oriented computing and Web services are

becoming more and more popular, enabling organizations to use

the Web as a market for selling their own Web services and consuming

existing Web services others. Nevertheless, with the

increasing adoption and presence of Web services, it becomes

more difficult to find the most appropriate Web service that satisfies

both users’ functional and nonfunctional requirements. In

this paper, we propose an effective Web service ranking approach

based on collaborative filtering (CF) by exploring the user behavior,

in which the invocation and query history are used to infer

the potential user behavior. CF-based user similarity is calculated

through similar invocations and similar queries (including

functional query and QoS query) between users.-Abstract—Service-oriented computing and Web services are

becoming more and more popular, enabling organizations to use

the Web as a market for selling their own Web services and consuming

existing Web services　others. Nevertheless, with the

increasing adoption and presence of Web services, it becomes

more difficult to find the most appropriate Web service that satisfies

both users’ functional and nonfunctional requirements. In

this paper, we propose an effective Web service ranking approach

based on collaborative filtering (CF) by exploring the user behavior,

in which the invocation and query history are used to infer

the potential user behavior. CF-based user similarity is calculated

through similar invocations and similar queries (including

functional query and QoS query) between users.