A Survey of Topic Evolution Based on LDA
Fang Li · Zhongwen xinxi xuebao · 2010
With topics evolve over time,new topics emerge and old ones decay.Many researches are devoted to detect the topic evolution automatically.Latent Dirichlet Allocation(LDA),as a recently emerged probabilistic topic model,has been widely used in the research of topic evolution.This paper discusses two aspects of evolution on topic,i.e.the content and the topic intensity.It summarizes three methods in LDA based topic evolution detection according to the dealing with time: joining the time to LDA model,post-discretizing or pre-discretizing methods.The three methods are also compared in several features: the time granularity,on-line or off-line,etc.In addition,the evaluation methods for topic evolution are introduced.Finally,the paper gives some analysis and suggestions for future researches on topic evolution based on LDA.