Efficient text summarization method for blind people using text mining techniques-Reference-Cited by-同舟云学术

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Efficient text summarization method for blind people using text mining techniques

Published:2020-06-11 Issue:4 Volume:23 Page:713-725
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Basheer Shakila,Anbarasi M.^ORCID,Sakshi Darpan Garg,Vinoth Kumar V.

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Link

https://link.springer.com/content/pdf/10.1007/s10772-020-09712-z.pdf

Reference55 articles.

1. Aliguliyev, R. M. (2007). Automatic document summarization by sentence extraction. Computing Technology, 12(5), 5–15.

2. Allahyari, M., Pouriyeh, S., Assefi, M., Safaei, S., Trippe, E. D., Gutierrez, J. B., & Kochut, K. (2017). Text summarization techniques: a brief survey. arXiv:1707.02268.

3. Aone, C., Okurowski, M. E., & Gorlinsky, J. (1998, August). Trainable, scalable summarization using robust NLP and machine learning. In Proceedings of the 17th international conference on Computational linguistics-Volume 1 (pp. 62–66). Association for Computational Linguistics.

4. Barzilay, R., & Elhadad, N. (2002). Inferring strategies for sentence ordering in multi document news summarization. Journal of Artificial Intelligence Research, 17, 35–55.

5. Barzilay, R., & Lee, L. (2003, May). Learning to paraphrase: An unsupervised approach using multiple-sequence alignment. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1 (pp. 16–23). Association for Computational Linguistics.

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