Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 6
1697-1701

Self-adaptive affinity graph learning for short text matching

Fu Cong
Li Liuwu
Yang Zhenguo
Liu Wenyin
School of Computer Science, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2018.12.0877

Abstract

For text matching problems in natural language processing, this paper proposed a deep learning model based on self-adaptive affinity graph learning framework for short text matching. The affinity graph can be converted into a vector form using word embedding, and then obtained by constructing a text similarity relationship matrix, which can express the neighbor relationship of the text sample. Current methods usually construct static affinity graphs, which rely on prior knowledge and hard to obtain the optimal representation of sentence pairs. Therefore, this paper proposed using the Siamese CNN to learn the affinity graph of better dynamic updates. The accuracy and F1 values of the model on the Quora dataset are 84.15% and 79.88%, and on the MSRP dataset are 74.55% and 81.63%. Experiments show that the proposed model can improve the accuracy of text recognition and matching effectively.

Foundation Support

国家自然科学基金资助项目(61703109,91748107)
中国博士后科学基金资助项目(2018M643024)
广东省引进创新科研团队计划资助项目(2014ZT05G157)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.12.0877
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 6
Section: Algorithm Research & Explore
Pages: 1697-1701
Serial Number: 1001-3695(2020)06-019-1697-05

Publish History

[2020-06-05] Printed Article

Cite This Article

付聪, 李六武, 杨振国, 等. 基于自学习近邻图策略的短文本匹配方法 [J]. 计算机应用研究, 2020, 37 (6): 1697-1701. (Fu Cong, Li Liuwu, Yang Zhenguo, et al. Self-adaptive affinity graph learning for short text matching [J]. Application Research of Computers, 2020, 37 (6): 1697-1701. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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