Survey on Resume Screening Mechanisms

International Journal of Computer Science and Engineering

© 2022 by SSRG - IJCSE Journal

Volume 9 Issue 4

Year of Publication : 2022

Authors : Tumula Mani Harsha, Gangaraju Sai Moukthika, Dudipalli Siva Sai, Mannuru Naga Rajeswari Pravallika, Satish Anamalamudi

10.14445/23488387/IJCSE-V9I4P103

How to Cite?

Tumula Mani Harsha, Gangaraju Sai Moukthika, Dudipalli Siva Sai, Mannuru Naga Rajeswari Pravallika, Satish Anamalamudi, "Survey on Resume Screening Mechanisms," SSRG International Journal of Computer Science and Engineering , vol. 9,  no. 4, pp. 14-22, 2022. Crossref, https://doi.org/10.14445/23488387/IJCSE-V9I4P103

Abstract:

Resume Screening is the primary step in the hiring process. It evaluates the candidates' resumes and determines whether they are qualified for a role based on their education, skill sets, technical stuff, experience, and other information captured in their resume. To make it simple, it's a form of pattern that matches the job requirement and the candidate's qualifications based on their resume. It is a crucial step in the process of hiring. It is the step in which a decision is made to move the candidate to the next level or not. There are multiple processes to perform resume screening. Among all the processes, traditional resume or manual screening is the largest followed, even today. But usually, companies receive thousands of resumes for job applications, which consumes a lot of time and effort. In addition to this, many errors may arise due to human involvement. Multiple ways were introduced to cover all these cons to performing this resume screening process. Various technologies, including Artificial Intelligence and Machine Learning, were involved in searching for solutions. This paper contains a detailed survey report on various methodologies and techniques of resume screening.

Keywords:

Resume Screening, Artificial Intelligence, Machine Learning, Hiring.

References:

[1] Rutuja Patil, Pratiksha Sarvade, Ajinkya Patil, Yash Bhosale, “Resume Evaluation System Based on AI,” International Research Journal of Engineering and Technology, vol. 7, no. 7, 2020.
[2] V. V. Dixit, Trisha Patel, Nidhi Deshpande, Kamini Sonawane, “Resume Sorting using Artificial Intelligence,” International Journal of Research in Engineering, Science and Management, vol. 2, no. 4, 2019.
[3] Pradeep Kumar Roy, Sarabjeet Singh Chowdhary, Rocky Bhatia, “A Machine Learning Approach for Automation of Resume Recommendation System, Procedia Computer Science, vol. 167, pp. 2318-2327, 2020.
[4] Gaurav Dutta, Resume Screening Using Machine Learning, 2021.
[5] “Resume Screening Using Deep Learning on Cainvas,” AI Technologies and Systems, 2021. 
[6] Aman Kharwal, “Machine Learning Project on Resume Screening with Python,” Resume Screening with Python, 2021.
[7] Fresh Works, Resume Screening - How to Stop Swimming in a Sea of Resumes? 2016.
[8] Roberto Salazar, “Analyzing Candidates Resumes for Jobs Openings,” Resume Screening with Python, 2020.
[9] Iqbal, Z., Qadir, J., Mian, A. N., & Kamiran, F, “Machine Learning Based Student Grade Prediction: A Case Study,” Computers and Society, 2017. Arxiv Preprint Arxiv:1708.08744.
[10] Vadivu, G., K. Sornalakshmi, “Applying Machine Learning Algorithms for Student Employability Prediction Using R,” International Journal of Pharmaceutical Sciences Review and Research, pp. 38-41, 2017.
[11] Kim, B. H., Vizitei, E., & Ganapathi, V, Gritnet: Student Performance Prediction with Deep Learning., Arxiv Preprint Arxiv:1804.07405, 2018.
[12] Xu, J., Moon, K. H., & Van Der Schaar, M, “ A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs,” IEEE Journal of Selected Topics in Signal Processing, vol. 11, no. 5, pp. 742-753, 2017.
[13] Mrs. Sayantanighosh, Mr. Sudipta Roy, and Prof. Samir K. Bandyopadhyay, “A Tutorial Review on Text Mining Algorithms,” In International Journal of Advanced Research in Computer and Communication Engineering, vol. 1, 2012.
[14] Vishal Gupta, Gurpreet S. Lehal, “A Survey of Text Mining Techniques and Applications,” In Journal of Emerging Technologies in Web Intelligence, vol. 1, no. 1, 2009.
[15] Falguni N. Patel, Neha R. Soni, “Text Mining: A Brief Survey," International Journal of Advanced Computer Research (ISSN (Print): 2249-7277 ISSN (Online): 2277-7970.
[16] Jadhav, Amrut M., and Devendra P. Gadekar, “A Survey on Text Mining and Its Techniques,” International Journal of Science and Research (IJSR), vol. 3, no. 11, 2014.
[17] N. Kanya and S. Geetha, “Information Extraction: A Text Mining Approach,” IET-UK International Conference on Information and Communication Technology in Electrical Sciences, IEEE, Dr. M.G.R. University, Chennai, Tamil Nadu, India, pp. 1111- 1118, 2007.
[18] S. M. Weiss, N. Indurkhya, T. Zhang, and F. Damerau, Text Mining: Predictive Methods for Analyzing Unstructured Information. (Springerscience and Business Media, 2010.
[19] Liritano S. and Ruffolo M, “ Managing the Knowledge Contained in Electronic Documents: A Clustering Method for Text Mining,” IEEE, pp. 454-458, 2011. Italy.
[20] Deepshikha Patel, Monika Bhatnagar, “Mobile SMS Classification,” International Journal of Soft Computing and Engineering (IJSCE) ,ISSN: 2231-2307 (Online), vol. 1, no. 1, 2011.
[21] Ms. Anushree Negi, “A Brief Survey on Text Mining, Its Techniques, and Applications,” SSRG International Journal of Mobile Computing and Application, vol. 8, no. 1, pp. 1-6, 2021.Doi:10.14445/23939141/IJMCA-V8I1P101
[22] Chetan Arora, Mehrdad Sabetzadeh, Lionel Briand & Frank Zimmer, “Automated Checking of Conformance to Requirements Templates Using Natural Language Processing,” IEEE Transactions on Software Engineering, vol. 41, no. 10, pp. 1-1.
[23] Julia Hirschberg, Bruce W. Ballard, and Donald Hindle, Natural Language Processing.
[24] Minhwa Chung and D. Moldevan, Applying Parallel Processing to Natural-Language Processing, IEEE , 1994.
[25] B. W. Wah and T. S. Huang, Report on Workshop on High-Performance Computing and Communications for Grand Challenge Applications: Computer Vision, Speech, and Natural Language Processing, and Artificial Intelligence, IEEE Transactions on Knowledge and Data Engineering, 1993.