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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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2083-2567
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Order Estimation of Japanese Paragraphs by Supervised Machine Learning and Various Textual Features

Masaki Murata
  • Department of Information and Electronics, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan
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/ Satoshi Ito
  • Department of Information and Electronics, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan
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/ Masato Tokuhisa
  • Department of Information and Electronics, Tottori University, 4-101 Koyama-Minami, Tottori 680-8552, Japan
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/ Qing Ma
  • Department of Applied Mathematics and Informatics, Ryukoku University Seta, Otsu, Shiga 520-2194, Japan
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-10-29 | DOI: https://doi.org/10.1515/jaiscr-2015-0033

Abstract

In this paper, we propose a method to estimate the order of paragraphs by supervised machine learning. We use a support vector machine (SVM) for supervised machine learning. The estimation of paragraph order is useful for sentence generation and sentence correction. The proposed method obtained a high accuracy (0.84) in the order estimation experiments of the first two paragraphs of an article. In addition, it obtained a higher accuracy than the baseline method in the experiments using two paragraphs of an article. We performed feature analysis and we found that adnominals, conjunctions, and dates were effective for the order estimation of the first two paragraphs, and the ratio of new words and the similarity between the preceding paragraphs and an estimated paragraph were effective for the order estimation of all pairs of paragraphs.

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About the article

Published Online: 2015-10-29

Published in Print: 2015-10-01


Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 5, Issue 4, Pages 247–255, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2015-0033.

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© 2015. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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