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人工智能时代科技期刊应对学术不端问题的研究进展
引用本文:曾玲,张辉洁,冉明会,唐宗顺,罗萍,王维朗. 人工智能时代科技期刊应对学术不端问题的研究进展[J]. 浙江预防医学, 2020, 31(3): 270-405. DOI: 10.11946/cjstp.201911030753
作者姓名:曾玲  张辉洁  冉明会  唐宗顺  罗萍  王维朗
作者单位:1) 重庆医科大学期刊社,重庆市沙坪坝区大学城中路61号 4013312) 重庆大学期刊社,重庆市沙坪坝区沙正街174号 400044
摘    要:【目的】 探讨当前人工智能时代下,科技期刊利用智能工具、大数据自动挖掘技术、人工智能分析技术,对存在的和可能发生的学术不端问题采取的相应措施。【方法】 根据目前常见的学术不端行为特征,分析学术不端检测软件的检索现状、人工智能辅助同行评审的方式,以及审稿人身份的检测等,梳理人工智能可以参与的过程,并提出相应措施及未来的方向。【结果】 基于人工智能的学术搜索引擎、智能图像数据库,可在同行评审时引入智能分析,将区块链技术运用到实验数据记录、同行评审中,采用身份唯一识别代码、用户画像功能鉴别作者、审稿人身份等。【结论】 人工智能与出版行业融合发展是未来的方向,具有较大的发展潜力和成长空间,科技期刊需要在智能时代运用更多智能工具,在学术不端行为的预防和控制方面作出更多的努力,以发挥更大的作用。

关 键 词:人工智能  学术不端  科技期刊  剽窃  伪造和篡改  虚假同行评审  区块链  用户画像  
收稿时间:2019-11-03

Research progress on scientific journals dealing with academic misconduct in the era of artificial intelligence
ZENG Ling,ZHANG Huijie,RAN Minghui,TANG Zongshun,LUO Ping,WANG Weilang. Research progress on scientific journals dealing with academic misconduct in the era of artificial intelligence[J]. Zhejiang Journal of Preventive Medicine, 2020, 31(3): 270-405. DOI: 10.11946/cjstp.201911030753
Authors:ZENG Ling  ZHANG Huijie  RAN Minghui  TANG Zongshun  LUO Ping  WANG Weilang
Affiliation:1) Periodical Press of Chongqing Medical University, 61 Middle University Road, Shapingba District, Chongqing 401331, China2) Journal Press of Chongqing University, 174 Shazhengjie, Shapingba District, Chongqing 400044, China
Abstract:[Purposes] This study aims to explore the appropriate countermeasures which scientific journals take to solve the existing and possible problems of academic misconduct in the scientific research by using intelligent tools, automatic data mining technology, and artificial intelligence analysis technology in the era of artificial intelligence. [Methods] According to the characteristics of current academic misconducts, we analyzed the current status of academic misconduct detection software, the way of artificial intelligence assisted peer review, and the detection of reviewer identity, sorted the process that artificial intelligence can participate in, and put forward corresponding countermeasures and future directions. [Findings] The artificial intelligence-based academic search engine and intelligent image database can introduce intelligent analysis during peer review, and apply blockchain technology in experimental data recording and peer review process. The unique identification code and user portrait function are used to identify the author and reviewer status. [Conclusions] The integrative development of artificial intelligence and the publishing industry is the future direction with strong development potential and growth space. Scientific journals need to use intelligent tools in the intelligent era to make efforts in the prevention and control of academic misconduct.
Keywords:Artificial intelligence  Academic misconduct  Scientific journal  Plagiarism  Forgery and falsification  False peer review  Blockchain  User portrait  
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