文献类型：期刊文献

中文题名：基于Topsis思想的内容推荐算法研究

英文题名：Research on Content-Based Recommendation Based on the Idea of Topsis

作者：刘玲[1]

第一作者：刘玲

机构：[1]河南财经政法大学工商管理学院

第一机构：河南财经政法大学工商管理学院

年份：2012

卷号：24

期号：16

起止页码：113-119

中文期刊名：数学的实践与认识

外文期刊名：Mathematics in Practice and Theory

收录：CSTPCD;;北大核心:【北大核心2011】；CSCD:【CSCD_E2011_2012】；

基金：河南省政府招标课题(2012B052)

语种：中文

中文关键词：推荐系统;基于内容推荐;Topsis方法;相似度

外文关键词：recommender systems; content-based recommendation; topsis method; similar-ity

摘要：针对内容推荐系统中的瓶颈问题——特征表示问题,将特征属性进行了排序,并利用高斯函数获得产品的属性取值.进而借助Topsis中理想解与负理想解的思想定义了产品在各个属性上的相似性,并通过Topsis中属性间的可补偿性获得了产品间的相似度.
Focused on the trouble of the features representation of merchandise in Contentbased Recommendation system. In this paper, the features were ranked with their important. Meanwhile, with Gaussian function, the indexes of features were obtained. With the ideM solution and negative ideal solution of Topsis, the similarity of each feature of product was de- fined. Finally, the similarity between the products was get by the attribute of compensatory in Topsis method.