Abstract
More and more Web services raise the demands of personalized service recommendation; there exist some recommendation technologies, which improve the qualities of service recommendation by using service ranking and collaborative filtering. However, privacy and security are also important issues in service scheduling process; social relationships have been the key factors of interpersonal communication; service selection based on user preferences has become an inevitable trend. Starting from user demand preferences, this paper analyzes social topology and service demand information and obtains trusted social relationships; then we construct the fusion model of service historical preferences and potential ones; according to social service recommendation demands, TSRSR algorithm has completed designing. Through experiments, TSRSR algorithm is much better than the others, which can effectively improve potential preferences’ learning. Furthermore, the research results of this paper have more significance to study the security and privacy of service recommendation.
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