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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2081-2086

Sequence generation method based on adaptive learning

Zhang Baoqia,b,c
Zhao Shulianga,b,c
Zhang Jiana,b,c
Lyu Xiaofenga,b,c
a. College of Computer & Cyber Security, b. Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security, c. Hebei Provincial Key Laboratory of Network & Information Security, Hebei Normal University, Shijiazhuang 050024, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0681

Abstract

Discrete sequence generation is widely used in text generation, sequence recommendation and other fields. The current research work mainly focuses on improving the accuracy of sequence generation, but ignores the diversity of generation. To address this phenomenon, this paper proposed an adaptive sequence generation method(ECoT), and designed a two-layer meta controller. In the data layer, the function of meta controller was to realize adaptive learning sampling, automatically balance the distribution of real data and generated data, and obtain mixed data distribution. At the model level, this paper added diversity constraints. The function of the meta controller was to adaptively learn the optimal update gradient to improve the generation diversity of the generation model. In addition, in order to improve the accuracy of the generation model, this paper proposed a method combining cooperative training and adversarial learning. Compared with the current mainstream models, the results show that the adaptive cooperative training sequence generation method has more balanced accuracy and diversity in terms of generation accuracy and diversity, and can effectively alleviate the pattern collapse of the generation model.

Foundation Support

国家社会科学基金重大资助项目(13&ZD091,18ZDA200)
河北省重点研发计划项目(20370301D)
河北师范大学重大关键技术攻关项目(L2020K01)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0681
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Algorithm Research & Explore
Pages: 2081-2086
Serial Number: 1001-3695(2022)07-025-2081-06

Publish History

[2022-03-08] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

张宝奇, 赵书良, 张剑, 等. 基于自适应学习的序列生成方法 [J]. 计算机应用研究, 2022, 39 (7): 2081-2086. (Zhang Baoqi, Zhao Shuliang, Zhang Jian, et al. Sequence generation method based on adaptive learning [J]. Application Research of Computers, 2022, 39 (7): 2081-2086. )

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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