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Online fake job advertisement recognition and classification using machine learning
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- المؤلفون: Othman Alandjani, Gasim
- المصدر:
3 c TIC: cuadernos de desarrollo aplicados a las TIC, ISSN 2254-6529, Vol. 11, Nº. 1, 2022, pags. 251-267
- نوع التسجيلة:
Electronic Resource
- الدخول الالكتروني :
https://dialnet.unirioja.es/servlet/oaiart?codigo=8415586
- معلومة اضافية
- Publisher Information:
2022
- نبذة مختصرة :
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.
- الموضوع:
- Availability:
Open access content. Open access content
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- Note:
application/pdf
3 c TIC: cuadernos de desarrollo aplicados a las TIC, ISSN 2254-6529, Vol. 11, Nº. 1, 2022, pags. 251-267
English
- Other Numbers:
S9M oai:dialnet.unirioja.es:ART0001527600
https://dialnet.unirioja.es/servlet/oaiart?codigo=8415586
(Revista) ISSN 2254-6529
1343687472
- Contributing Source:
UNIV COMPLUTENSE DE MADRID
From OAIster®, provided by the OCLC Cooperative.
- الرقم المعرف:
edsoai.on1343687472
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