Algorithm Research & Explore
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1017-1021

Siamese bidirectional GRU attention model for humor text comparison

Gu Yan1
Xia Hongbin1,2
Liu Yuan1,2
1. School of Artificial Intelligence & Computer, Jiangnan University, Wuxi Jiangsu 214122, China
2. Jiangsu Key Laboratory of Media Design & Software Technology, Wuxi Jiangsu 214122, China

Abstract

Traditional humor computing tasks rely on artificially constructed features, which are prone to loss of features, and mainly focus on humorous judgment. The Siamese bidirectional GRU attention model based on deep learning compared pairs of humorous texts to determine which sentence was more humorous. Firstly, this paper used the text processor to train the word embedding. Secondly, it used the bidirectional GRU model to obtain the annotation of each word. Finally, it performed the humorous comparison task at the fully connected layer. This paper conducted experiments on the Semeval-2017 Task6-#HashtagWars data set, and used accuracy as an evaluation indicator. The experimental results show that the model and other related models have a significant improvement in the comparison of humorous text.

Foundation Support

国家科学支撑计划课题(2015BAH54F01)
国家自然科学基金资助项目(61672264)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.05.0118
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1017-1021
Serial Number: 1001-3695(2021)04-010-1017-05

Publish History

[2021-04-05] Printed Article

Cite This Article

顾艳, 夏鸿斌, 刘渊. 一种文本幽默对比的Siamese双向GRU注意力模型 [J]. 计算机应用研究, 2021, 38 (4): 1017-1021. (Gu Yan, Xia Hongbin, Liu Yuan. Siamese bidirectional GRU attention model for humor text comparison [J]. Application Research of Computers, 2021, 38 (4): 1017-1021. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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