基于人工神经网络的在线招聘欺诈检测

Ibrahim Nasser, Amjad H. Alzaanin, Ashraf Y. A. Maghari
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引用次数: 4

摘要

网上招聘为求职者提供了一个有效的搜索和找到工作的途径。它还可以帮助招聘人员寻找合格的候选人,从而改善招聘流程。然而,就业诈骗已成为一个关键问题。有些招聘广告是合法的,有些则是欺诈的。本文提出了一种基于人工神经网络的虚假招聘信息检测模型。公共就业骗局爱琴海数据集(EMSCAD)与适当的文本预处理技术一起用于训练和测试所提出的模型。模型的精密度、召回率和f-measure分别为91.84%、96.02%和93.88%。结果表明,基于人工神经网络的模型在检测欺诈作业方面优于现有的类似模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Recruitment Fraud Detection using ANN
Online recruitment provides job-seekers an efficient search and reach for jobs. It also helps recruiters searching for qualified candidates which improves the recruitment process. However, employment scam has emerged as a critical issue. Some job posts are legitimate, and others are fraud. In this paper, an Artificial Neural Network based model is proposed to detect fraud job posts. The public Employment Scam Aegean Dataset (EMSCAD) is used with proper text preprocessing techniques for training and testing the proposed model. Our model has precision, recall, and f-measure of 91.84%, 96.02%, and 93.88% respectively. The results show that the proposed ANN-based model outperforms similar existing models in detecting fraud jobs.
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