计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 137-139.

• 数据库与数据挖掘 • 上一篇    下一篇

面向移动终端的微博信息推荐方法

宋双永,李秋丹   

  1. (中国科学院自动化研究所复杂系统与智能科学重点实验室 北京100190)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Micro-blogging Information Recommendation System for Mobile Client

SONG Shuang-yong,LI Qiu-dan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 微型博客(简称“微博'')以其简洁方便的交互方式,受到越来越多手机用户的喜爱。然而,微博数据量大、更新速度快以及手机屏幕小、登录网络服务速度较慢等原因,使得用户很难通过移动终端快速了解到近期内微博流行内容。提出一种基于相关主题模型(correlated topic model)的移动微博信息推荐方法,并基于此方法设计了一个可视化移动信息推荐系统。通过‘用户一主题一词语’三维关联矩阵的建立,帮助用户快速了解最近一段时间内的热点主题,并查找与其感兴趣主题相关的其他用户作为备选好友,同时计算主题之间的关联关系,进行主题扩展。在微博代表性网站—Fricndfccd数据集上进行的实验表明了该方法在移动微博信息推荐中的简洁性和有效性。

关键词: 微型博客,相关主题模型,好友推荐,主题扩展,移动信息推荐

Abstract: As a new type of online community, micro-blogging has gained more and more attention from mobile users.The most favorite person, as well as understanding interesting themes have become the main reason why users visit micro-blogging. In this paper, we proposed a correlated topic model-based approach for information recommendation in micro-blogging system. The approach can automatically find the relationship among users, topics and words, from which we can get the hot topics in the most recent period, the most influential users about each topic, and the incidence relationamong those topics. Experiment results show that the method can provide mobile users with useful information related to their interest.

Key words: Micro-blogging, Correlated topic model, Friend recommendation, Topic expansion, Mobile information recommendation

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