针对农产品移动信息服务的需求,结合分类算法和个性化推荐算法,提出了一种基于分类的推荐算法.利用决策树分类方法对农产品进行分类,获得分类后的数据,采用协同过滤算法分析分类数据,查找兴趣相似的用户,将感兴趣的农产品信息推荐给正在使用系统的用户.实验结果表明:与传统的推荐方法及相比,该系统向用户推荐了兴趣度更高的农产品移动信息.
Aimed at mobile information services of agricultural products,combined with personalized recommendation algorithm and classification algorithm,provided a the recommend algorithm based on classification. use of decision tree classification method for classifying agricultural products,obtaining classified data,use of collaborative filtering algorithms analyze categorical data and look for similar user interest,recommend produce information to the user. Experimental results show that the traditional method and compared recommendation,the system recommended a higher degree of interest in agricultural information to mobile users.