STRATEGIC IMPLEMENTATION OF RANDOM FOREST  TO  DETECT  JOB  SCAM

Shreevyshali G; Pranauv M; Sinega R; Swetha R; Satheesh Kumar D

STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM

May 2024

Vol-10, Issue-3

Paper ID: 23966

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science Engineering

Keywords

Scam indicators Random forest classifier Natural Language Processing Feature detection Supervised Learning Fake employment listings Classification accuracy Performance metrics

Abstract

In these desperate times, when thousands Scammers are taking benefit of the economic crisis on the internet by producing fake employment listings that seem real. These fraud artists imitate real firms' hiring practices and produce convincing corporate websites. On the opposite hand, thorough examination could differentiate between these hoaxes personal information during interviews are common signs of fraud. Given the current state of the economy, a lot of desperate job searchers could ignore these red flags and fall victim to these frauds. It's critical to find phony employment postings among the many promos in order to prevent falling for scams and real opportunities. Missing corporate logos, first correspondence from illegitimate email accounts, and necessitate for sensitive data

License

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Author Information

#	Name	Institute / Affiliation
1	Shreevyshali G	Hindusthan College of Engineering and Technology
2	Pranauv M	Hindusthan College of Engineering and Technology
3	Sinega R	Hindusthan College of Engineering and Technology
4	Swetha R	Hindusthan College of Engineering and Technology
5	Satheesh Kumar D	Hindusthan College of Engineering and Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

G, Shreevyshali, M, Pranauv, R, Sinega, R, Swetha, & D, Satheesh Kumar (2024). STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 2383-2389.

MLA Style

G, Shreevyshali, et al. "STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 2383-2389.

IEEE Style

Shreevyshali G, Pranauv M, Sinega R, Swetha R, and Satheesh Kumar D, "STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 2383-2389, 2024.

Vancouver Style

G Shreevyshali, M Pranauv, R Sinega, R Swetha, D Satheesh Kumar. STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):2383-2389.

Harvard Style

G, Shreevyshali, M, Pranauv, R, Sinega, R, Swetha, & D, Satheesh Kumar (2024) 'STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 2383-2389.

Chicago Style

G, Shreevyshali, et al. "STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 2383-2389.

Turabian Style

G, Shreevyshali, et al. "STRATEGIC IMPLEMENTATION OF RANDOM FOREST TO DETECT JOB SCAM." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 2383-2389.