A personalized recommendation system based on case intelligence
Jianyang Li, Rui Li, Jinbin Zheng, Zhihong Zeng · 2010
The acquisition of personalized need is key to effective recommendation. Case intelligence is a comprehensive expression which is integrated representation of human sense, logics and creativity. Through the former cases we can acquire users' preferences which are implicit in case-base, the process of recommendation is easy to understand and accept. As E-commerce is in complex environment, cases are regarded as the foundation for knowledge representation in case intelligent system and may be represented in semi-structured or unstructured model, or even in natural language texts. This paper presents a personalized recommendation system based on case intelligence. The system has good flexibility, uses modular components to integrate various artificial intelligence technologies, which is convenient to acquire revision knowledge from huge cases from multi-channels. At last, this article proposes how to explore the revision knowledge and characteristic adaptation methods, so we can improve the quality of recommendation and “support” the users effectively.