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	LDA-based model for topic evolution mining on text
	Wu, Qingqiang ; Deng, Xiang ; Zhang, Caidong ; Jiang, Changlong ; Wu QQ(吴清强)
	2011
关键词	Computer science Education computing Semantics
英文摘要	Conference Name:6th International Conference on Computer Science and Education, ICCSE 2011. Conference Address: Singapore, Singapore. Time:August 3, 2011 - August 5, 2011.; A text mining model for topical evolutionary analysis was proposed through a text latent semantic analysis process on textual data. Analyzing topic evolution through tracking the topic different trends over time. Using the LDA model for the corpus and text to get the topics, and then using Clarity algorithm to measure the similarity of topics in order to identify topic mutation and discover the topic hidden in the text. Experiments show that the proposed model can discover meaningful topical evolution. ? 2011 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/ICCSE.2011.6028792
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/85849]
专题	软件学院－会议论文
推荐引用方式 GB/T 7714	Wu, Qingqiang,Deng, Xiang,Zhang, Caidong,et al. LDA-based model for topic evolution mining on text. 2011-01-01.

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