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Algorithm Research & Explore
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1388-1393

Dense passage retrieval model based on query semantic characteristics

Zhao Tiezhu1
Lin Lunkai1
Yang Qiuhong2
1. School of Computer Science & Technology, Dongguan University of Technology, Dongguan Guangdong 523808, China
2. School of Artificial Intelligence, Dongguan City University, Dongguan Guangdong 523419, China

Abstract

Addressing the issues of low negative sampling efficiency and tendency towards overfitting in existing dense passage retrieval(DPR) models, this paper proposed a DPR model based on query semantic characteristics(Q-DPR). Firstly, it introduced a negative sampling method based on neighbor queries for the negative sampling process. This method constructed high-quality negative samples rapidly by retrieving neighboring queries, thereby reducing the training costs. Secondly, to mitigate overfitting, it proposed a query self-supervised method based on contrastive learning. This method alleviated overfitting to training labels by establishing a self-supervised contrastive loss among queries, thereby enhancing retrieval accuracy. Q-DPR performed exceptionally well on the large-scale MSMARCO dataset for open-domain question answering, achieving a mean reciprocal rank of 0.348 and a recall rate of 0.975. Experimental results demonstrate that this model successfully reduces training overhead while also improving retrieval performance.

Foundation Support

广东省普通高校重点领域专项资助项目(2021ZDZX3007)
东莞市社会发展科技资助项目(20231800936732)
东莞城市学院青年教师发展基金资助项目(2022QJY005Z)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0412
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Algorithm Research & Explore
Pages: 1388-1393
Serial Number: 1001-3695(2024)05-016-1388-06

Publish History

[2023-11-21] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

赵铁柱, 林伦凯, 杨秋鸿. 基于查询语义特性的稠密文本检索模型 [J]. 计算机应用研究, 2024, 41 (5): 1388-1393. (Zhao Tiezhu, Lin Lunkai, Yang Qiuhong. Dense passage retrieval model based on query semantic characteristics [J]. Application Research of Computers, 2024, 41 (5): 1388-1393. )

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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