ONLINE FAKE JOB ADVERTISEMENT RECOGNITION AND CLASSIFICATION USING MACHINE LEARNING

被引:0
|
作者
Alandjani, Gasim Othman [1 ]
机构
[1] Yanbu Univ Coll, Comp Sci & Engn Dept, Yanbu, Saudi Arabia
来源
3C TIC | 2022年 / 11卷 / 01期
关键词
Machine learning; Supervised algorithms; Fake jobs detection; Classification;
D O I
10.17993/3ctic.2022.111.251-267
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Machine learning algorithms handle numerous forms of data in real-world intelligent systems. With the advancement in technology and rigorous use of social media platforms, many job seekers and recruiters are actively working online. However, due to data and privacy breaches, one can become the target of perilous activates. The agencies and fraudsters entice the job seekers by using numerous methods, sources coming from virtual job-supplying websites. We aim to reduce the quantity of such fake and fraudulent attempts by providing predictions using Machine Learning. In our proposed approach, multiple classification models are used for better detection. This paper also presents different classifiers' performance and compares results to enhance the results through various techniques for realistic results.
引用
收藏
页码:251 / 266
页数:16
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