Fake Job Prediction Using Machine Learning
Keywords:
NLP, Text Mining, Sentiment Analysis, Feature Extraction, Location-Based Features, Machine Learning Models, Fraud Indicators, Behavioral Analysis, Validation Techniques, Data Preprocessing, Geospatial Analysis, Web Scraping, User Feedback Analysis, Feature Engineering, Model Interpretability, Continuous Monitoring, Collaborative Filtering, Anomaly Detection, Supervised Learning, Unsupervised Learning, Classification AlgorithmsAbstract
Fake job listing detection is an interesting topic for computer scientists and social science. The recentgrowth of the online social fake job postings has great impact to the society. There is huge information fromdisparate sources among various users around the world. Developing a technique that can detect fake job postingsfrom these platforms is becoming a necessary
References
B. Alghamdi and F. Alharby, ―An Intelligent Model for Online Recruitment Fraud Detection,” J. Inf. Secur., vol. 10, no. 03, pp. 155–176, 2019, doi: 10.4236/jis.2019.103009.
I. Rish, ―An Empirical Study of the Naïve Bayes Classifier An empirical study of the naive Bayes classifier,‖ no. January 2001, pp. 41–46, 2014.
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Published
2024-06-07
How to Cite
Mr. R. Sreedhar, C.Sai Nithya, Bodukuriwar Shivani, Jangam Pushpa Latha. (2024). Fake Job Prediction Using Machine Learning. Journal of Computational Analysis and Applications (JoCAAA), 33(06), 1748–1755. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2508
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