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| New Words Discovery in Microblog Content |
| HUO Shuai, ZHANG Min, LIU Yi-Qun, MA Shao-Ping |
State Key Laboratory of Intelligent Technology and Systems, Beijing 100084
Tsinghua National Laboratory for Information Science and Technology, Beijing 100084
Department of Computer Science and Technology, Tsinghua University, Beijing 100084 |
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Abstract New words discovery is of great significance in the field of natural language processing. It is more difficult to find new words in microblog than in other corpus. In this paper, an algorithm based on context entropy is proposed, and the new word candidates are filtered based on the context. To improve the precision, lexical features are introduced and an algorithm combining them with term frequency is put forward. Thus, the precision rate and the recall rate are greatly improved, and the F-measure value is up to 89.6%.
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Received: 13 May 2013
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2014, Vol. 27 
