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DOI: 10.14569/IJACSA.2016.070250
PDF

Improving Quality of Vietnamese Text Summarization Based on Sentence Compression

Author 1: Ha Nguyen Thi Thu
Author 2: Tu Nguyen Ngoc
Author 3: Cuong Nguyen Ngoc
Author 4: Hiep Xuan Huynh

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 2, 2016.

  • Abstract and Keywords
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Abstract: Sentence compression is a valuable task in the framework of text summarization. In previous works, the sentence is reduced by removing redundant words or phrases from original sentence and tries to remain information. In this paper, we propose a new method that used Grid Model and dynamic programming to calculate n-grams for generating the best sentence compression. These reduced sentences are combined to text summarization. The experimental results showed that our method really effective and the text is grammatically, coherence and concise.

Keywords: Sentence compression; topic modeling; text summarization; Grid model; n-grams; dynamic programming

Ha Nguyen Thi Thu, Tu Nguyen Ngoc, Cuong Nguyen Ngoc and Hiep Xuan Huynh, “Improving Quality of Vietnamese Text Summarization Based on Sentence Compression” International Journal of Advanced Computer Science and Applications(IJACSA), 7(2), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070250

@article{Thu2016,
title = {Improving Quality of Vietnamese Text Summarization Based on Sentence Compression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070250},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070250},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {2},
author = {Ha Nguyen Thi Thu and Tu Nguyen Ngoc and Cuong Nguyen Ngoc and Hiep Xuan Huynh}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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