摘要
随着社会的飞速发展,生活节奏不断加快,消费者逐渐开始注重购买服装的效率,对个性化服装的需求也在不断增加。所以,个性化服装推荐系统对于消费者和商家来说都尤为重要。本文利用皮尔森相关系数和矩阵分解的有关理论,在K-NN(k-Nearest Neighbor)算法和SVD(Singular Value Decomposition)算法的基础上构建基于局部SVD++的服装推荐算法。
With the rapid development of society,the pace of life has been accelerating,consumers gradually began to pay attention to the efficiency of the purchase of clothing,and the demand for personalized clothing is also increasing.As a result,personalized clothing recommendation system for consumers and businesses are particularly important.Based on the K-NN(k-Nearest Neighbor)algorithm and the SVD(Singular Value Decomposition)algorithm,the paper constructs a clothing recommendation algorithm on the basis of local SVD++.
作者
尹定乾
杨佳乐
金英花
YIN Ding-qian;YANG Jia-le;JIN Ying-hua(Jiangnan University School of Science,Wuxi 214122,China)
出处
《价值工程》
2018年第10期173-176,共4页
Value Engineering
关键词
智能推荐
服装推荐算法
加权矩阵
矩阵分解
协同过滤
intelligent recommendation
clothing recommendation algorithm
weighting matrix
matrix decomposition
collaborative filtering
