Multi-label Text Classification with Deep Neural Networks

Yun Chen; Bo Xiao; Zhiqing Lin; Cheng Dai; Zuochao Li; Liping Yan

doi:10.1109/ICNIDC.2018.8525817

Multi-label Text Classification with Deep Neural Networks

Yun Chen, Bo Xiao^*, Zhiqing Lin, Cheng Dai, Zuochao Li, Liping Yan

^*此作品的通讯作者

自动化学院

Beijing University of Posts and Telecommunications

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

9 引用（Scopus）

摘要

Text classification is a foundational task in natural language processing (NLP). Traditional methods rely heavily on human-designed features, while deep learning models based on neural networks can automatically capture contextual information. We explore and introduce various neural network architectures to extract information and key components in texts. An extensive set of experiments and comparisons on accuracy, speed, memory-consumption are conducted. Methods based on the proposed models won the first place in the Zhihu Machine Learning Challenge 2017. The code has been made publicly available.

源语言	英语
主期刊名	Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
出版商	Institute of Electrical and Electronics Engineers Inc.
页	409-413
页数	5
ISBN（电子版）	9781538660669
DOI	https://doi.org/10.1109/ICNIDC.2018.8525817
出版状态	已出版 - 6 11月 2018
活动	6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 - Guiyang, 中国期限: 22 8月 2018 → 24 8月 2018

出版系列

姓名	Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018

会议

会议	6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018
国家/地区	中国
市	Guiyang
时期	22/08/18 → 24/08/18

访问文件

10.1109/ICNIDC.2018.8525817

其它文件与链接

链接到 Scopus 的出版物

引用此

Chen, Y., Xiao, B., Lin, Z., Dai, C., Li, Z., & Yan, L. (2018). Multi-label Text Classification with Deep Neural Networks. 在 Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 (页码 409-413). 文章 8525817 (Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICNIDC.2018.8525817

Chen, Yun ; Xiao, Bo ; Lin, Zhiqing 等. / Multi-label Text Classification with Deep Neural Networks. Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 409-413 (Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018).

@inproceedings{c13b728a729348a59ad464f079606ff6,

title = "Multi-label Text Classification with Deep Neural Networks",

abstract = "Text classification is a foundational task in natural language processing (NLP). Traditional methods rely heavily on human-designed features, while deep learning models based on neural networks can automatically capture contextual information. We explore and introduce various neural network architectures to extract information and key components in texts. An extensive set of experiments and comparisons on accuracy, speed, memory-consumption are conducted. Methods based on the proposed models won the first place in the Zhihu Machine Learning Challenge 2017. The code has been made publicly available.",

keywords = "Deep Learning, Multi-label Classification, Natural Language Processing, Neural Network",

author = "Yun Chen and Bo Xiao and Zhiqing Lin and Cheng Dai and Zuochao Li and Liping Yan",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018 ; Conference date: 22-08-2018 Through 24-08-2018",

year = "2018",

month = nov,

day = "6",

doi = "10.1109/ICNIDC.2018.8525817",

language = "English",

series = "Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "409--413",

booktitle = "Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018",

address = "United States",

}

Chen, Y, Xiao, B, Lin, Z, Dai, C, Li, Z & Yan, L 2018, Multi-label Text Classification with Deep Neural Networks. 在 Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018., 8525817, Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018, Institute of Electrical and Electronics Engineers Inc., 页码 409-413, 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018, Guiyang, 中国, 22/08/18. https://doi.org/10.1109/ICNIDC.2018.8525817

Multi-label Text Classification with Deep Neural Networks. / Chen, Yun; Xiao, Bo; Lin, Zhiqing 等.
Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 409-413 8525817 (Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Multi-label Text Classification with Deep Neural Networks

AU - Chen, Yun

AU - Xiao, Bo

AU - Lin, Zhiqing

AU - Dai, Cheng

AU - Li, Zuochao

AU - Yan, Liping

PY - 2018/11/6

Y1 - 2018/11/6

N2 - Text classification is a foundational task in natural language processing (NLP). Traditional methods rely heavily on human-designed features, while deep learning models based on neural networks can automatically capture contextual information. We explore and introduce various neural network architectures to extract information and key components in texts. An extensive set of experiments and comparisons on accuracy, speed, memory-consumption are conducted. Methods based on the proposed models won the first place in the Zhihu Machine Learning Challenge 2017. The code has been made publicly available.

AB - Text classification is a foundational task in natural language processing (NLP). Traditional methods rely heavily on human-designed features, while deep learning models based on neural networks can automatically capture contextual information. We explore and introduce various neural network architectures to extract information and key components in texts. An extensive set of experiments and comparisons on accuracy, speed, memory-consumption are conducted. Methods based on the proposed models won the first place in the Zhihu Machine Learning Challenge 2017. The code has been made publicly available.

KW - Deep Learning

KW - Multi-label Classification

KW - Natural Language Processing

KW - Neural Network

UR - http://www.scopus.com/inward/record.url?scp=85058286644&partnerID=8YFLogxK

U2 - 10.1109/ICNIDC.2018.8525817

DO - 10.1109/ICNIDC.2018.8525817

M3 - Conference contribution

AN - SCOPUS:85058286644

T3 - Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018

SP - 409

EP - 413

BT - Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018

Y2 - 22 August 2018 through 24 August 2018

ER -

Chen Y, Xiao B, Lin Z, Dai C, Li Z, Yan L. Multi-label Text Classification with Deep Neural Networks. 在 Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 页码 409-413. 8525817. (Proceedings of 2018 6th IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2018). doi: 10.1109/ICNIDC.2018.8525817

Multi-label Text Classification with Deep Neural Networks

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