A review of semi-supervised learning for text classification-Reference-Cited by-同舟云学术

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A review of semi-supervised learning for text classification

Published:2023-01-31 Issue:9 Volume:56 Page:9401-9469
ISSN:0269-2821
Container-title:Artificial Intelligence Review
language:en
Short-container-title:Artif Intell Rev

Author:

Duarte José Marcio,Berton Lilian

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Link

https://link.springer.com/content/pdf/10.1007/s10462-023-10393-8.pdf

Reference188 articles.

1. Abdali S, Shah N, Papalexakis E (2021) Semi-supervised multi-aspect detection of misinformation using hierarchical joint decomposition. In: Machine learning and knowledge discovery in databases. Applied data science and demo track. ECML PKDD 2020, pp 406–422. ISBN 978-3-030-67669-8

2. Abdi L, Hasehmi S (2021) Binary domain adaptation with independence maximization. Int J Mach Learn Cybern 12:09

3. Abonizio QH, Junior BS (2020) Pre-trained data augmentation for text classification. In: Intelligent systems, 2020. Springer, pp 551–565. ISBN 978-3-030-61377-8

4. Agarwal R (2021) Phrases based document classification from semi supervised hierarchical LDA. In: 2021 2nd International conference on computation, automation and knowledge management (ICCAKM), 2021, pp 332–337

5. Aghakhani H, Machiry A, Nilizadeh S, Kruegel C, Vigna G (2018) Detecting deceptive reviews using generative adversarial networks. In: 2018 IEEE security and privacy workshops (SPW), 2018, pp 89–95

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