基于用户的农产品协同过滤推荐系统的设计与实现

作为缓解信息过载问题的主要手段,个性化推荐技术已经得到广泛的应用。随着农产品电子商务技术的发展,如何将最新的个性化推荐技术应用到农产品的推荐,促进农产品电子商务的发展,是一个非常重要的问题。本文在对电子商务推荐系统原理分析基础上,重点深入探讨了当前应用最为广泛的协同过滤推荐技术。在此基础上,针对农产品的特点,设计并实现了一个基于用户的农产品电子商务协同过滤推荐系统。为提高用户评分的积极性,系统采用一定的激励评分机制,以缓解数据稀疏性问题。系统界面简洁,操作简单,实现了对农产品的有效推荐。

The Design and Implementation of Agricultural Product Collaborative Filtering Recommendation System Based on Users

As the main means to alleviate information overload, personalized recommendation technology has been widely applied. With the development of e-commerce technology for agricultural products, it has become a main problem in that how to apply the newest personalized recommendation technology in the recommendation of agricultural products. Based on the analysis of e -commerce principles, The thesis focused on the discuss of collaborative filtering recommendation model which was widely used at present. Then on the basis of characteristics of agricultural e-commerce, the collaborative filtering recommendation system with users oriented was developed and implemented. To raise the enthusiasm of users in rating, this system mainly took the adoption of certain incentive scoring mechanism. The system interface was simple and easy to operate, which achieved effective recommendation of agricultural products.