计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 214-219.doi: 10.11896/j.issn.1002-137X.2016.10.041
郑喆君,金蓓弘,崔艳玲
ZHENG Zhe-jun, JIN Bei-hong and CUI Yan-ling
摘要： 微博是一种社交网络服务,它主要基于用户的关注关系进行信息分享和传播,具有时效性强、传播迅速等特点。将微博看成是反映城市动态的一类感知器,从识别微博的主题入手,检测微博中反映的时空事件。为此,首先提出了一种用于分析微博主题的主题模型ST-LDA,并应用该模型将具有语义相似性、时空聚集性的微博归属于同一主题下；然后给出了从主题中检测时空事件的方法。基于真实的新浪微博数据进行实验,结果表明此方法比基于LDA的方法、基于TimeLDA的方法在事件识别上有更高的查全率和查准率。
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