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The implementation of knowledge-based recommender system for electronic commerce using Java expert system library

机译:使用Java专家系统库实现基于知识的电子商务推荐系统

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This paper deals the design and implementation of product recommender system on a Internet shopping mall. In e-commerce application, sometimes potential buyers may be interested in receiving recommendations about what to purchase. The mainstream of an automated recommender system is collaborative filtering. In this paper, we present a knowledge-based product recommender system. The knowledge base of product domain and inference engine is implemented by JESS (Java expert system shell) and Java servlet. The system gathers the user's requirements on a particular product by questioning the user and consulting its knowledge base to find the items that best meet the user's requirement. For the recommender system, the design of product knowledge base are discussed. As a sample implementation, a cellular phone recommender system is built where the system tries to find a phone model that best meets the user's requirements.
机译:本文论述了网上商城产品推荐系统的设计与实现。在电子商务应用程序中,有时潜在的买家可能会对接收有关购买商品的建议感兴趣。自动化推荐系统的主流是协作过滤。在本文中,我们提出了一个基于知识的产品推荐系统。产品领域和推理引擎的知识库由JESS(Java专家系统外壳)和Java Servlet实现。该系统通过询问用户并咨询其知识库以找到最能满足用户需求的项目,从而收集用户对特定产品的需求。对于推荐系统,讨论了产品知识库的设计。作为示例实现,构建了蜂窝电话推荐器系统,其中该系统尝试查找最能满足用户要求的电话型号。

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