PCFinder: An Intelligent Product Recommendation Agent for E-Commerce

There are many e-commerce applications on the web. A common shortcoming is the lack of customer service and marketing analysis tools in most ecommerce web sites. In order to overcome this problem, we have constructed an intelligent agent based on Case-Based Reasoning (CBR) and collaborative filtering, which we have included in our product recommendation system, called PCFinder. This system was four main characteristics. The first is applying novel methodologies based on CBR to an e-commerce application. We propose a heuristic to represent an Order-Based Similarity Measure, together with the method of weight modification and adaptation. The second is applying CBR and collaborative filtering techniques to make our intelligent agent more efficient and effective. We also apply clustering analysis techniques to assist our intelligent agent for grouping the customers according to their long-term profiles in order to analyse the user profiles (external attributes) and provide some suggestion...

• Type: Conference
• Year: 2003
• Where: WECWIS
• Authors: Bin Xiao, Esma Aïmeur, José Manuel Fernandez
• Keywords: Business, Collaborative Filtering, Intelligent Agent, Product Recommendation Systems, WECWIS 2003