Feature selection based on long short term memory for text classification-Reference-Cited by-同舟云学术

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Feature selection based on long short term memory for text classification

Published:2023-10-18 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Hong Ming,Wang Heyong^ORCID

Funder

Natural Science Foundation of Guangdong Province for Distinguished Young Scholars

Guangzhou Office of Philosophy and Social Science

Guangdong Philosophy and Social Science

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-16990-7.pdf

Reference121 articles.

1. Abdi A, Shamsuddin S, Hasan MS et al (2019) Deep learning-based sentiment classification of evaluative text based on multi-feature fusion. Inf Process Manage 56(4):1245–1259

2. Abdullah M, Hadzikadic M, Shaikh S (2018) SEDAT: sentiment and emotion detection in Arabic text using CNN-LSTM deep learning. In: Proceedings of 17th IEEE international conference on machine learning and applications (IEEE ICMLA), Orlando, pp 835–840

3. Abdur R, Kashif J, Haroon AB (2017) Feature selection based on a normalized difference measure for text classification. Inf Process Manage 53:473–489

4. Adel A, Omar N, Abdullah S, Al-Shabi A (2022) Co-operative binary bat optimizer with rough set reducts for text feature selection. Appl Sci-Basel 12(21):1–35

5. Agnihotri D, Verma K, Tripathi P (2017) Variable global feature selection scheme for automatic classification of text documents. Expert Syst Appl 81:268–281

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