An intelligent recommender derived from its characteristic case revision
Yanhai Zhao, Jianyang Li, Xiuzheng Xie · 2010
Through the wide use of E-commerce, the acquisition of personalized need is key to effective recommender. From the view of knowledge acquiring, case intelligence is a comprehensive expression which is integrated representation of human sense, logics and creativity, and can acquire the user's preferences from the former stored cases. As the E-commerce is under much complex conditions, this paper presents a personalized recommender based on case intelligence, which processes the same similar knowledge reasoning. Besides, compared with the most used collaborative filtering recommendation system, both the first user-based and the second item-based recommender, our system can be executing with the same similarity as their citing criteria. The article proposes a new reasoning structure integrated by various artificial intelligent technologies to acquire personalized knowledge. Finally, the case adaptation is described to explore the revision knowledge from huge cases through multi-channel accesses, which can guarantee the reliability and integrity of the adapting process.