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AUTOMATED PRODUCT RECOMMENDATION BY EMPLOYING CASE-BASED REASONING AGENTS

机译:通过采用基于案例的推理代理商自动化产品推荐

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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.
机译:本文提出了一种合作框架,用于多种基于角色的基于案例的推理(CBR)代理商,用于处理电子商务应用程序的产品推荐问题。每个代理具有不同的案例结构,具有交叉功能,代理通过合作利用与问题相关的所有信息,这是通过分布式案例的合并来实现的。基于角色的CBR Agent通过引入全球启发式函数来合并分布式函数,该函数利用每个代理的角度和满足/不满的问题约束的每个合并案例的相关性。最后,已经测试了拟议的框架,用于选修课程建议。

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