模糊逻辑在电子商务商品推荐系统中的应用

在电子商务平台中提供有针对性的商品推荐机制以帮助用户快速准确地找到所需的商品非常重要。综合满意度是指根据用户关注的商品的不同属性的满意度在商品推荐中所占的权重不同,对商品的各属性满意度进行加权运算得到的满意度度量值。根据商品综合满意度的排序进行商品的推荐可以提高推荐的准确性。商品满意度是一个模糊的概念,提出了使用模糊逻辑来处理商品满意度的方法,并提出了一整套基于满意度的商品推荐机制。论文介绍了一个基于商品满意度的电子商务商品推荐系统的框架,重点介绍了其中的基于模糊逻辑的商品属性满意度处理方法和基于商品综合满意度的商品推荐规则,并给出了一个商品推荐的模拟实例。

Application of Fuzzy Logic to E-Commerce Recommendation System of Commodity

In e-commerce platform to provide targeted product recommendation mechanism to help users quickly and accurately find the merchandise is very important. Comprehensive Satisfaction is the focus of the product based on user satisfaction with different attributes of the commodity the weight recommended in the different properties of the satisfaction of all goods operations by the weighted measure of satisfaction.Comprehensive Satisfaction according to the sort of goods where goods are recommended to improve the accuracy of recommendation. Product satisfaction is a vague concept, this paper proposes the use of fuzzy logic to handle goods satisfaction methods, and proposed a set of recommendations based on product satisfaction mechanism. This paper introduces a commodity-based e-commerce product satisfaction recommendation system framework, which focuses on product attributes based on fuzzy logic approach and satisfaction with Comprehensive Satisfaction based on commodity products recommended by the rules, and gives a recommendation of goods Simulation instance.