Abstract: Topic evolution means the changes of contents and strength of a topic over time. This paper first gives the definition of topic evolution, describes two methods of topic evolution based on global and local documents. Two metrics of topic similarity and perplexity are used to evaluate both methods. The evolutions of the two topics (the real estate vs. the 2008 Olympic games) are analyzed. The experiments on the recent five years of NPC&CPPCC news reports show that topic evolution based on global documents can get good topic model, the evolution method is easy, while topic evolution based on local documents can produce fine topics and show the arising of new topics and the vanishing of old topics.  

Key words: text information processing, latent dirichlet allocation, topic detection and evolution