【摘要】 协同过滤推荐方法在传统个性化推荐领域被广泛使用。农资电子商务领域面向的专家/终端用户和批发/零售的混合模式更为复杂,需要对传统协同过滤方法加以改进。文章在传统协同过滤模型基础上,提出对用户兴趣建模动态调整,改进K最近邻算法,以满足农资电子商务领域的特殊需求。实验证明,在农资个性化推荐中使用基于改进协同过滤的方法,提高了推荐的质量和效率。更多还原

【Abstract】 The Collaborative filtering recommendation method is widely used in traditionally personalized recommendation domain.Because the e-commerce of agricultural production supplies,which mixes expert users and end users,wholesale and retail,is more complex,and it is necessary to improve the algorithm.Based on the traditional collaborative filtering method,the dynamic adjustment of user interest modeling and the improvement scheme of K nearest neighbor algorithm are proposed to meet the specific needs of recommendation in E-agriculture recommender system.Experiments show that the improved collaborative filtering method improve the quality and efficiency of recommendation in E-agriculture recommender system.更多还原