A Review of Machine Learning Algorithms for Text Classification

Ruiguang Li; Ming Liu; Dawei Xu; Jiaqi Gao; Fudong Wu; Liehuang Zhu

doi:10.1007/978-981-16-9229-1_14

A Review of Machine Learning Algorithms for Text Classification

Ruiguang Li^*, Ming Liu, Dawei Xu, Jiaqi Gao, Fudong Wu, Liehuang Zhu

^*Corresponding author for this work

School of Cyberspace Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

Text classification is a basic task in the field of natural language processing, and it is a basic technology for information retrieval, questioning and answering system, emotion analysis and other advanced tasks. It is one of the earliest application of machine learning algorithm, and has achieved good results. In this paper, we made a review of the traditional and state-of-the-art machine learning algorithms for text classification, such as Naive Bayes, Supporting Vector Machine, Decision Tree, K Nearest Neighbor, Random Forest and neural networks. Then, we discussed the advantages and disadvantages of all kinds of machine learning algorithms in depth. Finally, we made a summary that neural networks and deep learning will become the main research topic in the future.

Original language	English
Title of host publication	Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers
Editors	Wei Lu, Yuqing Zhang, Weiping Wen, Hanbing Yan, Chao Li
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	226-234
Number of pages	9
ISBN (Print)	9789811692284
DOIs	https://doi.org/10.1007/978-981-16-9229-1_14
Publication status	Published - 2022
Event	18th China Cyber Security Annual Conference, CNCERT 2021 - Beijing, China Duration: 20 Jul 2021 → 21 Jul 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1506 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	18th China Cyber Security Annual Conference, CNCERT 2021
Country/Territory	China
City	Beijing
Period	20/07/21 → 21/07/21

Keywords

Machine learning
Natural language processing
Neural network
Text classification

Access to Document

10.1007/978-981-16-9229-1_14

Cite this

Li, R., Liu, M., Xu, D., Gao, J., Wu, F., & Zhu, L. (2022). A Review of Machine Learning Algorithms for Text Classification. In W. Lu, Y. Zhang, W. Wen, H. Yan, & C. Li (Eds.), Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers (pp. 226-234). (Communications in Computer and Information Science; Vol. 1506 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-9229-1_14

Li, Ruiguang ; Liu, Ming ; Xu, Dawei et al. / A Review of Machine Learning Algorithms for Text Classification. Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers. editor / Wei Lu ; Yuqing Zhang ; Weiping Wen ; Hanbing Yan ; Chao Li. Springer Science and Business Media Deutschland GmbH, 2022. pp. 226-234 (Communications in Computer and Information Science).

@inproceedings{ef1adbd536d54fcf8314580f5241ae72,

title = "A Review of Machine Learning Algorithms for Text Classification",

abstract = "Text classification is a basic task in the field of natural language processing, and it is a basic technology for information retrieval, questioning and answering system, emotion analysis and other advanced tasks. It is one of the earliest application of machine learning algorithm, and has achieved good results. In this paper, we made a review of the traditional and state-of-the-art machine learning algorithms for text classification, such as Naive Bayes, Supporting Vector Machine, Decision Tree, K Nearest Neighbor, Random Forest and neural networks. Then, we discussed the advantages and disadvantages of all kinds of machine learning algorithms in depth. Finally, we made a summary that neural networks and deep learning will become the main research topic in the future.",

keywords = "Machine learning, Natural language processing, Neural network, Text classification",

author = "Ruiguang Li and Ming Liu and Dawei Xu and Jiaqi Gao and Fudong Wu and Liehuang Zhu",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).; 18th China Cyber Security Annual Conference, CNCERT 2021 ; Conference date: 20-07-2021 Through 21-07-2021",

year = "2022",

doi = "10.1007/978-981-16-9229-1_14",

language = "English",

isbn = "9789811692284",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "226--234",

editor = "Wei Lu and Yuqing Zhang and Weiping Wen and Hanbing Yan and Chao Li",

booktitle = "Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers",

address = "Germany",

}

Li, R, Liu, M, Xu, D, Gao, J, Wu, F & Zhu, L 2022, A Review of Machine Learning Algorithms for Text Classification. in W Lu, Y Zhang, W Wen, H Yan & C Li (eds), Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers. Communications in Computer and Information Science, vol. 1506 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 226-234, 18th China Cyber Security Annual Conference, CNCERT 2021, Beijing, China, 20/07/21. https://doi.org/10.1007/978-981-16-9229-1_14

A Review of Machine Learning Algorithms for Text Classification. / Li, Ruiguang; Liu, Ming; Xu, Dawei et al.
Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers. ed. / Wei Lu; Yuqing Zhang; Weiping Wen; Hanbing Yan; Chao Li. Springer Science and Business Media Deutschland GmbH, 2022. p. 226-234 (Communications in Computer and Information Science; Vol. 1506 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Review of Machine Learning Algorithms for Text Classification

AU - Li, Ruiguang

AU - Liu, Ming

AU - Xu, Dawei

AU - Gao, Jiaqi

AU - Wu, Fudong

AU - Zhu, Liehuang

PY - 2022

Y1 - 2022

N2 - Text classification is a basic task in the field of natural language processing, and it is a basic technology for information retrieval, questioning and answering system, emotion analysis and other advanced tasks. It is one of the earliest application of machine learning algorithm, and has achieved good results. In this paper, we made a review of the traditional and state-of-the-art machine learning algorithms for text classification, such as Naive Bayes, Supporting Vector Machine, Decision Tree, K Nearest Neighbor, Random Forest and neural networks. Then, we discussed the advantages and disadvantages of all kinds of machine learning algorithms in depth. Finally, we made a summary that neural networks and deep learning will become the main research topic in the future.

AB - Text classification is a basic task in the field of natural language processing, and it is a basic technology for information retrieval, questioning and answering system, emotion analysis and other advanced tasks. It is one of the earliest application of machine learning algorithm, and has achieved good results. In this paper, we made a review of the traditional and state-of-the-art machine learning algorithms for text classification, such as Naive Bayes, Supporting Vector Machine, Decision Tree, K Nearest Neighbor, Random Forest and neural networks. Then, we discussed the advantages and disadvantages of all kinds of machine learning algorithms in depth. Finally, we made a summary that neural networks and deep learning will become the main research topic in the future.

KW - Machine learning

KW - Natural language processing

KW - Neural network

KW - Text classification

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DO - 10.1007/978-981-16-9229-1_14

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SN - 9789811692284

T3 - Communications in Computer and Information Science

SP - 226

EP - 234

BT - Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers

A2 - Lu, Wei

A2 - Zhang, Yuqing

A2 - Wen, Weiping

A2 - Yan, Hanbing

A2 - Li, Chao

PB - Springer Science and Business Media Deutschland GmbH

T2 - 18th China Cyber Security Annual Conference, CNCERT 2021

Y2 - 20 July 2021 through 21 July 2021

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Li R, Liu M, Xu D, Gao J, Wu F, Zhu L. A Review of Machine Learning Algorithms for Text Classification. In Lu W, Zhang Y, Wen W, Yan H, Li C, editors, Cyber Security - 18th China Annual Conference, CNCERT 2021, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 226-234. (Communications in Computer and Information Science). doi: 10.1007/978-981-16-9229-1_14

A Review of Machine Learning Algorithms for Text Classification

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