摘要
首先在分析微博文本特点的基础上设计了一种垃圾微博的过滤算法;针对微博数据稀疏性这一问题,利用社区内部联系紧密的特性,提出了微博评论树的概念和一种话题热度评价模型。最后基于以上两点提出了一种微博社区热门话题检测方法。真实数据集上的实验表明了过滤的必要性和所提出的微博社区热门话题检测方法的有效性。
Firstly,this paper analyzed the characteristics of the micro-blog text and designed a filtering algorithm of garbage micro-blog. Then,in order to solve the problem of data sparsity,taking full advantage of the feature of community tightness,this paper proposed the concept of micro-blog comments tree and an evaluation model of hot topic. Finally,based on the two points above,it proposed a hot topic detection method on micro-blog community. Experiments on real data sets show that the necessity of the filtering algorithm and the validity of hot topic evaluation model and hot topic detection method.
出处
《计算机应用研究》
CSCD
北大核心
2014年第12期3776-3779,3827,共5页
Application Research of Computers
基金
国家"863"计划资助项目(2011AA010603
2011AA010605)
关键词
微博社区
热门话题
过滤
评论树
话题热度评价模型
micro-blog community
hot topic
filtering
comments tree
hot topic evaluation model
