利用组合模型生成微博热点话题事件摘要

针对微博热点话题检测使用主题模型只能提取出无序话题词组合的问题,提出一种结合词激活力模型与主题模型各自优点的微博热点话题检测方法及话题关键词的计算方法。首先,使用传统的主题模型提取出微博文本中的热点主题；其次,根据各主题下文档的概率分布提取出新的话题文档；然后引入词激活力模型计算各个词之间的词激活力,生成词激活力矩阵；最后,利用词激活力矩阵生成有序的词序列作为热点事件。实验验证了该方法的可行性,表明所提出方法能够很好地识别出热点词并生成可读性高的事件。

Hot topic summarization on microblog generated by model combination

To solve the problem that microblog hot topic detection based on topic model can only extract disorderly words combinations, a hot topic detection method on microblog combined with the advantage of word active force model and topic model, as well as its calculation method of Keywords, is proposed. Firstly, this approach extracts hot topic on microblog through topic model. Secondly, new documents are extracted according to the probability distribution of documents under each topic. Then, the word active matrix is generated by word active model. Finally, an orderly sequence of words as hot topic is generated by word active matrix. The experiments prove the feasibility of the proposed method which can effectively identify topic Keywordsand generate events with high readability.