Text mining, bug reports, topic mining, co-evolution

Author(s):  
Olga Baysal ◽  
Ian Davis ◽  
Michael W. Godfrey
Keyword(s):  
2021 ◽  
Author(s):  
Uy Nguyen ◽  
Kowk Sun Cheng ◽  
Samuel Sungmin Cho ◽  
Myoungkyu Song

2016 ◽  
Vol 8 (4) ◽  
pp. 100-113 ◽  
Author(s):  
Xiongwen Pang ◽  
Benshuai Wan ◽  
Huifang Li ◽  
Weiwei Lin

Latent Dirichlet Allocation(LDA) is an efficient method of text mining,but applying LDA directly to Chinese micro-blog texts will not work well because micro-blogs are more social, brief, and closely related with each other. Based on LDA, this paper proposes a Micro-blog Relation LDA model (MR-LDA), which takes the relations between Chinese micro-blog documents and other Chinese micro-blog documents into consideration to help topic mining in micro-blog. The authors extend LDA in the following two points. First, they aggregate several Chinese micro-blogs as a single micro-blog document to solve the problem of short texts. Second, they model the generation process of Chinese micro-blogs more accurately by taking relationship between micro-blog documents into consideration. MR-LDA is more suitable to model Chinese micro-blog data. Gibbs sampling method is borrowed to inference the model. Experimental results on actual datasets show that MR-LDA model can offer an effective solution to text mining for Chinese micro-blog.


2013 ◽  
Author(s):  
Ronald N. Kostoff ◽  
◽  
Henry A. Buchtel ◽  
John Andrews ◽  
Kirstin M. Pfiel

2020 ◽  
Vol 42 (5) ◽  
pp. 279-307
Author(s):  
Yonglim Joe
Keyword(s):  

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