标题：A Way to Construct Evolution Model of Scientific Papers Based on the Seed Document and OLDA Models
作者：Qiao, Shanzeng; Han, Aili
作者机构：[Qiao, Shanzeng; Han, Aili] Shandong Univ, Dept Comp Sci, Weihai 264209, Peoples R China.
会议名称：International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)
会议日期：DEC 20-22, 2013
来源：PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC)
关键词：natural language processing; topic evolution; topic model; OLDA; seed; document
摘要：Tracking the topic evolution in scientific papers is an important issue. This paper presents a topic evolution framework which is based on the seed document and Online Latent Dirichlet Allocation (OLDA) models. We define seed document and link the seed documents of current time slice into the documents of next slice to keep the continuity of topics in content. And then, we run the OLDA in each time slice and take the word-topic posterior probability in previous time slice as the word-topic prior probability in current time slice to keep the continuity of topics in timeline. The cosine measure is used to compute the topic similarity in the adjacent time slices to find the topic evolution. The experimental results show that the way can help find the topic evolution in continuous time.