中文摘要：

为了在面向服务计算环境中提供个性化的服务,提出了一种将基于贝叶斯网络的用户行为模型与基于向量空间模型的用户兴趣模型相结合进行推荐的算法。通过分析目前典型的个性化推荐算法的特点,提出了基于贝叶斯网络的用户行为模型,该模型能准确反映用户的执行动向。为了解决同种服务类型内多个服务的偏好问题,提出了基于向量空间模型的用户兴趣模型。通过分析表明,该个性化推荐算法有较好的推荐效果,可以满足用户不断变化的各种需求。

英文摘要：

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.