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	A topic description model based on two-layer KL distance
	Lin, Daz He ; Lin, Xian Min ; Cao, Dong Li ; Cao DL(曹冬林)
	2013
关键词	Mechanics
英文摘要	Conference Name:2013 2nd International Conference on Measurement, Instrumentation and Automation, ICMIA 2013. Conference Address: Guilin, China. Time:April 23, 2013 - April 24, 2013.; Korea Maritime University; Hong Kong Industrial Technology Research Centre; Inha University; The main challenge of Topic Detection and Tracking (TDT) for Blog is the insufficient information in a topic description and the lack of key words input by users. We propose a Two-layer KL Distance approach which combines the KL distance model with a lexical semantic association matrix model. First, the KL Distance model captured the weights of Initial feature words. Second, the KL Distance model was used again to estimate weights of words linked with initial feature words in the lexical Semantic Association Matrix. Extensive experiments show the advantages of our method over the baselines as well as the effectiveness of the two-layer of KL Distance. ? (2013) Trans Tech Publications, Switzerland.
语种	英语
出处	http://dx.doi.org/10.4028/www.scientific.net/AMM.333-335.791
出版者	Trans Tech Publications Ltd
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86634]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Lin, Daz He,Lin, Xian Min,Cao, Dong Li,et al. A topic description model based on two-layer KL distance. 2013-01-01.

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