A novel ensemble statistical topic extraction method for scientific publications based on optimization clustering

Author(s):  
Ammar Kamal Abasi ◽  
Ahamad Tajudin Khader ◽  
Mohammed Azmi Al-Betar ◽  
Syibrah Naim ◽  
Sharif Naser Makhadmeh ◽  
...  
Author(s):  
Takafumi Nakanishi ◽  
Ryotaro Okada ◽  
Yuichi Tanaka ◽  
Yutaka Ogasawara ◽  
Kazuhiro Ohashi

2011 ◽  
Vol 268-270 ◽  
pp. 1127-1131 ◽  
Author(s):  
Zhan Feng Sun ◽  
Kong Jun Bao

On the base of researching currently popular text topic extraction technologies, a new text topic automatic abstracting method is proposed based on rough set theory and rough similarity. Firstly it separated a text into words and sentences to complete information segmentation, and then constructed a similarity matrix by computing the rough similarity between different words to realize the text clustering, finally extracted representative sentences from each class to generate the text topic. The experiment shows that the method is feasible and effective.


Author(s):  
Ammar Kamal Abasi ◽  
Ahamad Tajudin Khader ◽  
Mohammed Azmi Al-Betar ◽  
Syibrah Naim ◽  
Zaid Abdi Alkareem Alyasseri ◽  
...  

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