摘要
随着农村电子商务的发展,农产品电商也慢慢进入人们的生活,在国家"互联网+"战略的推动下,农产品电子商务得到了快速发展,与此同时用户的个性化需求也渐渐地成为一种趋势。为了满足消费者的个性化的需求,提出针对农产品的改进协同过滤算法,其方法结合k-means算法,从而对聚类后的每个簇中的用户进行个性化推荐,此算法不仅可满足用户的个性化需求,而且在推荐产品的准确度和时间上有了较大的改善,进而帮助商家进行精准营销,提高农民收入。
With the development of rural electronic commerce,agricultural products manufacturers also slowly into people's lives,under the impetus of the national "Internet +"strategy,the electronic commerce of agricultural products has been developed rapidly,at the same time,the personalized demand of the users has gradually become a trend.In order to meet the personalized needs of consumers,this paper proposed an improved collaborative filtering algorithm for agricultural products,using K-means clustering to cluster users,personalized recommendation for users in each cluster,the proposed algorithm not only improves the platform construction,satisfies the user's demand,but also improves the accuracy and the time of the recommended product,and then helps the merchant to carry on the accurate marketing,enhances the farmer income.
出处
《邵阳学院学报（自然科学版）》
2017年第6期23-31,共9页
Journal of Shaoyang University：Natural Science Edition
基金
兰州财经大学甘肃商务发展研究中心项目(JYYY201506)
关键词
K-MEANS聚类
协同过滤
农产品
改进协同过滤
k-means clustering
collaborative filtration
agricultural products
improved collaborative filtration
