Personalized service recommendation algorithm in service-oriented environment

To provide users with personalized services in service oriented environment, a recommendation algorithm integrating a user behavior model based on Bayesian network and a user interest model based on vector space model was proposed. According to the analysis of the characteristics of typical personalized recommendation algorithms, a user behavior model based on Bayesian network was proposed which accurately reflected users' execution trend. To solve the preference problem of services in same service type, a user interest model based on vector space model was proposed. Analysis results demonstrated that this personalized recommendation algorithm had satisfactory effect and could meet various users' requirements.