计算机工程与应用Issue(20)：198-201,4.DOI:10.3778/j.issn.1002-8331.1206-0151
基于评分信息量的协同过滤算法研究
Collaborative filtering algorithm based on quantity of rating information
摘要
Abstract
Traditional collaborative filtering computes the similarity between users based on the rating value, however, the data sparseness causes the inaccurate of similarity computing. Aiming at this problem, this paper proposes a novel method based on quantity of rating information. It translates the amount of user who rates item with the same value to quantity of rating information, and combines the item-rating to calculate the similarity. The experimental results show that the proposed can relief the effect of data sparseness and improve the accuracy of predicted rating comparing to the traditional algorithm.关键词
相似度/评分用户数量/评分信息量/协同过滤Key words
similarity/amount of rating user/quantity of rating information/collaborative filtering分类
信息技术与安全科学引用本文复制引用
冯永,陈显勇..基于评分信息量的协同过滤算法研究[J].计算机工程与应用,2013,(20):198-201,4.基金项目
国家自然科学基金（No.61103114）；重庆市高等教育教学改革研究重点项目（No.112023）；中央高校基本科研业务基金（No.CDJXS11181164）；国家科技支撑计划（No.2012BAH19F001）。 （）
