摘要
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.
As the agriculture information developing, accessing information for agricultural users, cooperatives and agricultural companies. Combined with Chinese modem 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.
出处
《计算机系统应用》
2014年第3期83-87,共5页
Computer Systems & Applications
基金
十二五国家科技支撑计划(2012BAH20B00)
关键词
农资电子商务
推荐系统
内容过滤
用户兴趣
遗忘因子
agricultural e-commerce
recommendation system
content-based filtering
user preference
forgetting factor
