计算机工程2018，Vol.44Issue(3)：195-200,6.DOI:10.3969/j.issn.1000-3428.2018.03.033
基于多维相似度的利基产品推荐方法
Recommendation Method for Niche Product Based on Multi-dimensional Similarity
摘要
Abstract
Sales of the e-commerce platform possess a long tail character and niche products in the long tail are difficult to be involved in the list produced by the recommendation method whose goal is the pursuit of precision.Aiming at this problem,from the perspective of niche product,this paper proposes a new recommendation method.It calculates user ratings similarity,preferences similarity and latent features similarity between users based on rating information,attribute information and latent feature information respectively.Then,it excavates the possible users of the niche products that have the top similarity with the users who have high ratings for niche products based on the three similarities,and provids niche products for those possible users.Experimental results show that the recommendation conversion rate of the proposed method is much higher than probability matrix factorization method and collaborative filtering method for niche product recommendation.Therefore,it is more effective to solve the problem of niche products recommendation.关键词
推荐系统/长尾产品/利基产品/相似度计算/受众Key words
recommender system/long tail product/niche product/similarity calculation/possible user分类
信息技术与安全科学引用本文复制引用
刘业政,熊强,姜元春..基于多维相似度的利基产品推荐方法[J].计算机工程,2018,44(3):195-200,6.基金项目
国家自然科学基金重大项目(71490725) （71490725）
国家自然科学基金(91546114,71501057) （91546114,71501057）
国家科技支撑计划项目“第三方检验检测科技服务云平台研发及示范应用”(2015BAH26F00). （2015BAH26F00）
