基于内容过滤的农资电子商务推荐系统

随着农业信息化的发展，农业类网站已经成为农业用户、合作社和农资公司等获取信息的重要渠道．结合中国现代化农资经营电子商务平台，提出了基于内容过滤的推荐技术，采用四元组构建用户偏好模型，引入遗忘因子挖掘和更新偏好模型，并根据产品模型和用户偏好模型的相似度向用户推荐产品．实验结果表明，基于内容过滤的推荐算法可使农资电子商务平台的产品浏览率和购买率得到提高．

Content-Based Filtering Recommendation System in Agricultural E-commerce

As the agriculture information developing, agricultural websites have become an important channel for accessing information for agricultural users, cooperatives and agricultural companies. Combined with Chinese modern agricultural business e-commerce platform, content-based filtering recommendation technology is proposed, adopting four-tuple to construct user interest model, introducing forgetting factor to mining and update user preference, and generating recommendations depending on the similarity of product model and preference model. By the practical tests, the results show that Content-based filtering recommendation algorithm can effectively improve the purchase rate.