Neural Network Applications in Polygraph Scoring—A Scoping Review

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Dana Rad, Nicolae Paraschiv, Csaba Kiss
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引用次数: 0

Abstract

Polygraph tests have been used for many years as a means of detecting deception, but their accuracy has been the subject of much debate. In recent years, researchers have explored the use of neural networks in polygraph scoring to improve the accuracy of deception detection. The purpose of this scoping review is to offer a comprehensive overview of the existing research on the subject of neural network applications in scoring polygraph tests. A total of 57 relevant papers were identified and analyzed for this review. The papers were examined for their research focus, methodology, results, and conclusions. The scoping review found that neural networks have shown promise in improving the accuracy of polygraph tests, with some studies reporting significant improvements over traditional methods. However, further research is needed to validate these findings and to determine the most effective ways of integrating neural networks into polygraph testing. The scoping review concludes with a discussion of the current state of the field and suggestions for future research directions.
神经网络在测谎计分中的应用
测谎仪作为一种检测欺骗的手段已经使用了很多年,但是它的准确性一直是很多争论的主题。近年来,研究人员探索了神经网络在测谎评分中的应用,以提高测谎的准确性。本文的目的是对神经网络在测谎仪评分中的应用进行综述。本综述共检索和分析了57篇相关论文。对这些论文的研究重点、方法、结果和结论进行了审查。范围审查发现,神经网络在提高测谎仪测试的准确性方面显示出了希望,一些研究报告称,与传统方法相比,神经网络有了显著的改进。然而,需要进一步的研究来验证这些发现,并确定将神经网络整合到测谎仪测试中的最有效方法。最后讨论了该领域的现状,并对未来的研究方向提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
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