• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2013, Vol. 35 ›› Issue (10): 44-50.

• 论文 • 上一篇    下一篇

基于交互关系的微博用户标签预测

汪祥1,贾焰1,周斌1,陈儒华1,韩毅2   

  1. (1.国防科学技术大学计算机学院,湖南 长沙 410073;2.北京大学信息科学技术学院,北京 100871)
  • 收稿日期:2013-07-10 修回日期:2013-09-28 出版日期:2013-10-25 发布日期:2013-10-25
  • 基金资助:

    国家973计划资助项目(2013CB329601,2013CB329602,2013CB329604);国家863计划资助项目(2012AA01A401,2012AA01A402);国家自然科学基金资助项目(60933005,91124002);科技支撑计划课题(2012BAH38B04,2012BAH38B06);国家242信息安全计划资助项目(2011A010);博士后基金资助项目(2012M520114)

Interaction relation based user
tag prediction in Microblogging site         

WANG Xiang1,JIA Yan1,ZHOU Bin1,CHEN Ruhua1,HAN Yi2   

  1. (1.School of Computer Science,National University of Defense Technology,Changsha 410073;
    2.School of Information Science and Technology,Peking University,Beijing 100871,China)
  • Received:2013-07-10 Revised:2013-09-28 Online:2013-10-25 Published:2013-10-25

摘要:

在当今以用户贡献内容为核心的社交网络中,标签成为用户对资源进行标记和分类的重要依据。在新浪微博中,用户可以自由地给自己打上标签以表明自己的兴趣和特征等,用户标签在舆情分析与监测、广告推送和网络营销等应用中起到了非常重要的作用。针对新浪微博中绝大部分用户没有标签或标签较少的问题,提出了基于用户交互行为而产生的交互图的用户标签预测方法。在新浪微博用户量为1.4亿的真实数据集和大数据分析处理平台Hadoop上进行分析发现,本文提出的方法比当前常用的标签预测方法取得了更好的效果。关键词:

关键词: 标签预测, 微博, 交互关系, 标签推荐, 社交网络

Abstract:

In today’s social networks which take users as core, tags are important for users to mark or classify resources. In Sina microblogging website, user can freely tag himself (herself) to indicate his (her) interests and characteristics. User tags play an important role in network marketing, system recommendation and advertisement serving. For the issue that there are no tags or few tags for most users in Sina microblogging website, a method for tag prediction is proposed, which is based on interaction graph generated from actions of interaction between users. Experimental results on randomly generated test datasets show that our method for tag prediction gives better performance than the most used method.

Key words: tag prediction;microblogging;interaction relation;tag recommendation;social network