Submit your paper : editorIJETjournal@gmail.com Paper Title : A COMPARATIVE STUDY ON FAKE JOB POST PREDICTION USING DIFFERENT DATA MINING TECHNIQUES ISSN : 2395-1303 Year of Publication : 2022 10.5281/zenodo.7311183 MLA Style: -Mrs. N. Baby Rani, P. Anjani , P. Yasaswini , P.Kanaka Durga Bhavani A COMPARATIVE STUDY ON FAKE JOB POST PREDICTION USING DIFFERENT DATA MINING TECHNIQUES , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -Mrs. N. Baby Rani, P. Anjani , P. Yasaswini , P.Kanaka Durga Bhavani A COMPARATIVE STUDY ON FAKE JOB POST PREDICTION USING DIFFERENT DATA MINING TECHNIQUES , Volume 8 - Issue 5 September - October 2022 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract The study suggests an automated way of preventing bogus job postings online that uses categorization techniques based on machine learning. To determine the most effective model for identifying job scams, the output of multiple classifiers was compared. In order to verify false internet postings, these classifiers are used. In the midst of several other ads, it aids in identifying fraudulent job listings. The two fundamental categories of classifiers considered for the purpose. Reference [1] S.Vidros, C. Kolias , G. Kambourakis ,and L. Akoglu, “Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset”, Future Internet 2017, 9, 6; doi:10.3390/fi9010006. [2]B. Alghamdi, F. Alharby, “An Intelligent Model for Online Recruitment Fraud Detection”, Journal of Information Security, 2019, Vol 10, pp. 155176, https://doi.org/10.4236/iis.2019.103009 . [3]Tin Van Huynh1, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen1, and Anh Gia-Tuan Nguyen, “Job Prediction: From Deep Neural Network Models to Applications”, RIVF International Conference on Computing and Communication Technologies (RIVF), 2020. [4]Jiawei Zhang, Bowen Dong, Philip S. Yu, “FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural Network”, IEEE 36th International Conference on Data Engineering (ICDE), 2020. [5]Scanlon, J.R. and Gerber, M.S., “Automatic Detection of Cyber Recruitment by Violent Extremists”, Security Informatics, 3, 5, 2014, https://doi.org/10.1186/s13388-014-0005-5 [6]Y. Kim, “Convolutional neural networks for Sentence classification,” arXiv Prepr. arXiv1408.5882, 2014. [7] E. G. Dada, J. S. Bassi, H. Chiroma, S. M. Abdulhamid, A. O. Adetunmbi, and O. E. Ajibuwa, “Machine learning for email spam filtering: review, approaches and open research problems,‖ Heliyon, vol. 5, no. 6, 2019, doi: 10.1016/j.heliyon.2019.e01802. [8] L. Breiman, ―ST4_Method_Random_Forest,‖ Mach. Learn., vol. 45, no. 1, pp. 5–32, 2001, doi: 10.1017/CBO9781107415324.004. [9] B. Biggio, I. Corona, G. Fumera, G. Giacinto, and F. Roli, ―Bagging classifiers for fighting poisoning attacks in adversarial classification tasks,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 6713 LNCS, pp. 350–359, 2011, doi: 10.1007/978-3-642-21557-5_37. Keywords — A COMPARATIVE STUDY ON FAKE JOB POST PREDICTION USING DIFFERENT DATA MINING TECHNIQUES |