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@article{176368,
author = {Saloni Mittal and Saumya and Nawaal Parihar},
title = {ATS Resume},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {11},
number = {11},
pages = {7485-7491},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=176368},
abstract = {The increasing integration of technology in recruitment has led to widespread use of Applicant Tracking Systems (ATS) by employers to manage large volumes of job applications. These systems streamline the hiring process by automatically scanning, filtering, and ranking resumes based on specific criteria such as keywords, formatting, and relevance to the job description. As a result, job seekers are now required to tailor their resumes not only for human readability but also for machine compatibility to ensure they pass the initial screening.
This research paper explores the structure and characteristics of an ATS-optimized resume, comparing it with traditional formats in terms of performance and success rates. A detailed analysis was conducted using a controlled sample of resumes submitted to an ATS simulator. The results showed a clear advantage for resumes that followed ATS-friendly guidelines, particularly in parsing accuracy, keyword matching, and the likelihood of being shortlisted. The study underscores the growing importance of aligning resume content and design with the functionality of recruitment technology.
Beyond the technical aspects, the study also highlights broader implications for job seekers and HR professionals. With the continued evolution of hiring tools, understanding how ATS systems work can significantly impact employment outcomes. The findings encourage a shift toward data-driven, strategic resume writing and suggest areas for further research, including AI-based evaluation, algorithmic fairness, and sector-specific optimization strategies.},
keywords = {},
month = {April},
}
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