计算机应用研究2017，Vol.34Issue(9)：2718-2722,2726,6.DOI:10.3969/j.issn.1001-3695.2017.09.034
基于非负多矩阵分解的微博网络信息推荐
Information recommendation in microblogging network based on non-negative multiple matrix factorization
摘要
Abstract
As a popular form of social media,micro-blog Web site provides rich information and services to users,at the same time it also brings the problem of information overload.How to use the microblogging network to recommend valuable information for users,to ease the problem of information overload,becomes increasingly important.According to the orientation,the randomness followed and other characteristics in the microblogging network,this paper proposed a microblogging network recommendation based on non-negative multiple matrix factorization,comprehensively considering the follow relationship among users,the repost relationship between users and micro-blog content,and the ownership relationship between micro-blog content and topic and other multi-source information.Experiment on Sina Weibo dataset for the micro-blog content recommendation,the results show that the method based on non-negative multiple matrix factorization,can effectively use the multidimensional information in microblogging network,significantly improve the accuracy of recommendation.This method can not only dig out the theme of micro-blog content,but also dig out the relationship among users,and can be extended to recommend friends and topics to users.关键词
微博网络/推荐/非负多矩阵分解/好友/主题Key words
microblogging network/recommendation/non-negative multiple matrix factorization/friends/topics分类
信息技术与安全科学引用本文复制引用
张国英,武浩,蔡光卉,何敏,余江,徐涛..基于非负多矩阵分解的微博网络信息推荐[J].计算机应用研究,2017,34(9):2718-2722,2726,6.基金项目
云南省科技创新强省计划资助项目(2014AB016) （2014AB016）
国家自然科学基金资助项目(61562090) （61562090）
云南省应用基础研究计划面上项目(2013FB009) （2013FB009）
