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New Technology of Library and Information Service  2011, Vol. 27 Issue (7/8): 104-109    DOI: 10.11925/infotech.1003-3513.2011.07-08.17
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Topic Evolution Based on Seminal Document and Topic Model
Shan Bin, Li Fang
School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China
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Abstract  This paper presents a new method to infer the LDA topic evolution automatically based on seminal documents. The semantic distribution of the seminal documents is used to guide the successive model and link topics between consecutive time slices. The experiments are based on NIPS dataset and Chinese newswire of NPC and CPPCC,and the results show that the method can not only get the correct evolutions in various forms, but also avoid those related topics without evolution relationship.
Key wordsLDA      Topic evolution      Seminal document      Topic model     
Received: 11 May 2011      Published: 09 October 2011



Cite this article:

Shan Bin, Li Fang. Topic Evolution Based on Seminal Document and Topic Model. New Technology of Library and Information Service, 2011, 27(7/8): 104-109.

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