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Automated Product Recommendation by Employing Case-Based Reasoning Agents

This paper proposes a cooperation framework for multiple role-based case-based reasoning (CBR) agents to handle the product recommendation problem for e-commerce applications. Each agent has different case structure with intersecting features and agents exploit all information related to the problem by cooperation, which is accomplished through the merge of distributed cases. The role-based CBR agents merge the distributed cases by introducing a global heuristic function, which exploits the relevancy of each merged case within the viewpoint of each agent and the satisfied/unsatisfied problem constraints. Finally, the proposed framework has been tested for elective course recommendation.