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

I. Chun, In-Sik Hong
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引用次数: 23

Abstract

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.
利用Java专家系统库实现基于知识的电子商务推荐系统
本文研究了一个网上购物中心产品推荐系统的设计与实现。在电子商务应用中,有时潜在的购买者可能对收到关于购买什么的建议感兴趣。自动推荐系统的主流是协同过滤。本文提出了一个基于知识的产品推荐系统。产品领域知识库和推理引擎由Java专家系统外壳JESS和Java servlet实现。该系统通过询问用户并查询其知识库来收集用户对特定产品的需求,以找到最符合用户需求的产品。对于推荐系统,讨论了产品知识库的设计。作为一个示例实现,构建了一个手机推荐系统,系统试图找到最符合用户需求的手机型号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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