摘要
商务女装是女性的日常着装之一,很多女性在网购商务女装时常常花了很长的搜索时间却找不到令人满意的服装。本文将根据用户在搜索过程中常用的关键词类别进行调研,得到用户在网购时常用的关键词排序后,再根据关键词的内容进行细分,构建标签体系。根据TF-IDF和余弦相似算法构建基于标签的推荐系统,从而提高用户在购买商务女装时的精确度。
Business dress is one o f women＇s daily wear. However, many women shopping online spend longtime searching but can？ t find satisfying dress. Based on the keywords categories used most often in searching,a research has been carried out. Having got the keywords sorting which is subdivided according to the contento f the keywords, a tag system is established. According to TF-IDF and cosine sim ilarity algorithm, a tag-basedrecommendation system is built to improve the accuracy o f users buying business women ^ s wear.
出处
《浙江纺织服装职业技术学院学报》
2017年第4期68-72,共5页
Journal of Zhejiang Fashion Institute of Technology
关键词
标签推荐算法
用户兴趣
商务女装
个性化推荐系统
tag recommendation algorithm
user interest
women＇s business dress
personalized recommendationsystem
