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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 12
3640-3644

Chinese frame disambiguation based on frame representation learning

Hou Yunyao1a
Cao Xuefei1b
Cui Jun1a
Wang Ruibo1c
Li Jihong1b
Li Ru1a,2,3
1. a. School of Computer & Information Technology, b. School of software, c. School of Modern Educational Technology, Shanxi University, Taiyuan 030006, China
2. Key Laboratory of Computer Intelligence & Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, China
3. Collaborative Innovation Center of Big Data Mining & Intelligent Technology in Shanxi, Taiyuan 030006, China
DOI: 10.19734/j.issn.1001-3695.2019.09.0535

Abstract

In order to improve the performance of frame disambiguation model, this paper used a neural network model to learn frame representation based on sentences in corpus different from the traditional classification algorithm extracting features manually, and employed the learned frame representation on the frame disambiguation task, which significantly improved the performance of the task. Making full use of the CFN example sentence database and being based on the hinge-loss neural network, the algorithm learnt the frame representation that could distinguish the correct frame from the error frame in the largest degree. This paper also used the WSABIE algorithm to learn the representation vector of the context of the target word, and finally used the cosine distance between the context representation vector and the frame representation vector to make a decision for the task. Experiment performed three sets of two-fold cross-validation(3×2 BCV) on 88 ambiguous words in CFN, and the best accuracy of frame disambiguation reach to 72.52%. The t-test results show that the performance of the proposed method is significantly higher than other frame disambiguation methods.

Foundation Support

国家自然科学基金青年基金项目(61806115)
国家自然科学基金项目(61772324)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.09.0535
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 12
Section: Algorithm Research & Explore
Pages: 3640-3644
Serial Number: 1001-3695(2020)12-024-3640-05

Publish History

[2020-12-05] Printed Article

Cite This Article

侯运瑶, 曹学飞, 崔军, 等. 基于框架表示学习的汉语框架排歧 [J]. 计算机应用研究, 2020, 37 (12): 3640-3644. (Hou Yunyao, Cao Xuefei, Cui Jun, et al. Chinese frame disambiguation based on frame representation learning [J]. Application Research of Computers, 2020, 37 (12): 3640-3644. )

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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