计算机科学 ›› 2017, Vol. 44 ›› Issue (8): 270-273.doi: 10.11896/j.issn.1002-137X.2017.08.046
王振飞,刘凯莉,郑志蕴,王飞
WANG Zhen-fei, LIU Kai-li, ZHENG Zhi-yun and WANG Fei
摘要： 话题演化研究有助于追踪用户的喜好和话题的发展趋势,对于舆情预警具有重要意义。目前,话题演化方法注重运用话题生成模型实现话题演化分析,忽略了话题中时间因素和背景词的存在。以传统话题生成模型LDA为基础,将其扩展为微博话题生成模型MTLDA。MTLDA模型增加了对背景词的考虑,提高了话题生成的效率,同时对微博话题集进行时间片划分,利用KL距离计算相邻时间片话题距离,分析话题演化情况。以新浪微博数据为例进行实验,结果表明,MTLDA模型通过时间片划分完成了微博话题的生成,话题演化结果与实际情况吻合。
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