Tb-CNN: Joint tree-bank information for sentiment analysis using CNN

Tao Yang; Yang Li; Quan Pan; Lantian Guo

doi:10.1109/ChiCC.2016.7554468

Tb-CNN: Joint tree-bank information for sentiment analysis using CNN

Tao Yang, Yang Li, Quan Pan, Lantian Guo

School of Automation

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

11 Scopus citations

Abstract

Sentiment analysis still is a problem in text data analysis. In this paper, the proposed model which fuses the convolution neural network with the tree bank information has been introduced. This model not only takes into consideration of the syntax information, but also the structure information which is better than other single factor model. By a sequence of experiments, we can prove the goodness of this model in sentiment analysis.

Original language	English
Title of host publication	Proceedings of the 35th Chinese Control Conference, CCC 2016
Editors	Jie Chen, Qianchuan Zhao, Jie Chen
Publisher	IEEE Computer Society
Pages	7042-7044
Number of pages	3
ISBN (Electronic)	9789881563910
DOIs	https://doi.org/10.1109/ChiCC.2016.7554468
State	Published - 26 Aug 2016
Event	35th Chinese Control Conference, CCC 2016 - Chengdu, China Duration: 27 Jul 2016 → 29 Jul 2016

Publication series

Name	Chinese Control Conference, CCC
Volume	2016-August
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	35th Chinese Control Conference, CCC 2016
Country/Territory	China
City	Chengdu
Period	27/07/16 → 29/07/16

Keywords

Sentiment analysis
structure information
Tb-CNN

Access to Document

10.1109/ChiCC.2016.7554468

Cite this

@inproceedings{6711e25b9b064ae69451e18cb0eb13a4,

title = "Tb-CNN: Joint tree-bank information for sentiment analysis using CNN",

abstract = "Sentiment analysis still is a problem in text data analysis. In this paper, the proposed model which fuses the convolution neural network with the tree bank information has been introduced. This model not only takes into consideration of the syntax information, but also the structure information which is better than other single factor model. By a sequence of experiments, we can prove the goodness of this model in sentiment analysis.",

keywords = "Sentiment analysis, structure information, Tb-CNN",

author = "Tao Yang and Yang Li and Quan Pan and Lantian Guo",

note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",

year = "2016",

month = aug,

day = "26",

doi = "10.1109/ChiCC.2016.7554468",

language = "英语",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "7042--7044",

editor = "Jie Chen and Qianchuan Zhao and Jie Chen",

booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",

}

Yang, T, Li, Y , Pan, Q & Guo, L 2016, Tb-CNN: Joint tree-bank information for sentiment analysis using CNN. in J Chen, Q Zhao & J Chen (eds), Proceedings of the 35th Chinese Control Conference, CCC 2016., 7554468, Chinese Control Conference, CCC, vol. 2016-August, IEEE Computer Society, pp. 7042-7044, 35th Chinese Control Conference, CCC 2016, Chengdu, China, 27/07/16. https://doi.org/10.1109/ChiCC.2016.7554468

Tb-CNN: Joint tree-bank information for sentiment analysis using CNN. / Yang, Tao; Li, Yang ; Pan, Quan et al.
Proceedings of the 35th Chinese Control Conference, CCC 2016. ed. / Jie Chen; Qianchuan Zhao; Jie Chen. IEEE Computer Society, 2016. p. 7042-7044 7554468 (Chinese Control Conference, CCC; Vol. 2016-August).

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

TY - GEN

T1 - Tb-CNN

T2 - 35th Chinese Control Conference, CCC 2016

AU - Yang, Tao

AU - Li, Yang

AU - Pan, Quan

AU - Guo, Lantian

PY - 2016/8/26

Y1 - 2016/8/26

N2 - Sentiment analysis still is a problem in text data analysis. In this paper, the proposed model which fuses the convolution neural network with the tree bank information has been introduced. This model not only takes into consideration of the syntax information, but also the structure information which is better than other single factor model. By a sequence of experiments, we can prove the goodness of this model in sentiment analysis.

AB - Sentiment analysis still is a problem in text data analysis. In this paper, the proposed model which fuses the convolution neural network with the tree bank information has been introduced. This model not only takes into consideration of the syntax information, but also the structure information which is better than other single factor model. By a sequence of experiments, we can prove the goodness of this model in sentiment analysis.

KW - Sentiment analysis

KW - structure information

KW - Tb-CNN

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U2 - 10.1109/ChiCC.2016.7554468

DO - 10.1109/ChiCC.2016.7554468

M3 - 会议稿件

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T3 - Chinese Control Conference, CCC

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BT - Proceedings of the 35th Chinese Control Conference, CCC 2016

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PB - IEEE Computer Society

Y2 - 27 July 2016 through 29 July 2016

ER -

Tb-CNN: Joint tree-bank information for sentiment analysis using CNN

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Keywords

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