Service composition and user modeling for personalized recommendation in cloud computing In recent years, cloud computing is gradually evolving as a popular computing paradigm, which offers a uniform platform for service providers to publish their applications as cloud services. In many cases, however, single cloud service cannot satisfy a service request due to its simple functionality. Furthermore, current service composition systems have seldom taken into account user interests for personalized recommendation. In this paper, we propose a novel framework for personalized service recommendation in cloud computing platform by Web service composition and user modeling. The proposed framework first models cloud services together with a service request as a Web service composition problem, called cloud service recommendation (CSR) planning problem. It is fed into our self-developed service planner to compose a cloud service with complex business workflow. Second, our framework also applies user modeling for checking whether the generated composite cloud service can be matched with the interests of service consumer. To validate the feasibility of CSR framework, we have designed and implemented two prototype systems, QoS-aware service composition system and service platform based on user model.