Information push systems play an important role in reducing information overload for people visiting online sites, but their services could be improved by using data from online social networks, electronic communication tools and others. Information push systems are used by electronic commerce sites to suggest products to their customers and to provide consumers with information to help them determine which products to buy. There are many electronic commerce applications on the Web. A common shortcoming is the lack of customer service and marketing analysis tools in most electronic commerce websites. The paper presents the information push system using case-based reasoning. It introduces the case-based reasoning technology and analyzes the case representation, case library and case search. Lastly, it gives the architecture of the information push system using case-based reasoning.
An Electronic Commerce Recommendation Algorithm Joining Case-Based Reasoning and Collaborative Filtering
