Enhancing recruitment efficiency: An advanced Applicant Tracking System (ATS)
Prasad R. Chavan
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
Yash Chandurkar
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
Ankita Tidake
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
Gaurav Lavankar
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
Suhani Gaikwad
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
Rohit Chavan
Department of Artificial Intelligence and Data Science, Ajeenkya DY Patil School of Engineering
DOI: https://doi.org/10.59429/ima.v2i1.6373
Keywords: applicant tracking system, machine learning, natural language processing, KNN algorithm, job board, hiring lifecycles
Abstract
The Applicant Tracking System (ATS), also known as a talent management system or job applicant tracking system, is a software application designed to facilitate more efficient recruitment processes for companies or selection agencies. The objective of ATS is to streamline various aspects of the recruiting process, from receiving applications to hiring employees and effectively manage recruitment needs electronically. Methodologies such as NLP and KNN models are used for automated resume parsing and classifying the resume from unstructured format to structured format. The final results found significant improvement in performance of functionalities such as candidate screening, applicant testing, interview scheduling, managing the hiring process, reference checks, and completing new-hire paperwork.
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