Personalized recommendation services based on service-oriented architecture

Recommendation systems are special personalization tools that help users to find interesting information and services. This paper proposes a personalized recommendation system based on service-oriented architectures (SOAs). It introduces service-oriented recommendation technologies such as recommendation engines, data mining, content-based approach and collaborative filtering. It discusses service-oriented architecture, especially for service discovery and SOA for recommendation system. Then, it analyzes personalized recommendation system and proposes relative system architectures. Finally, it gives a case study about e-shop recommendation to illustrate the novel services.