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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

AI-POWERED INTERVIEW APPLICATION TRACKING SYSTEM (ATS): AN AI-POWERED RESUME ANALYSIS AND JOB MATCHING SYSTEM

Ritika Mehta Riya Rathore Naincy Sahu

Neeraj Paliwal

Indore Institute of Science and Technology, Indore

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

AI-Powered Interview Application Tracking System (ATS) is an AI-powered web application designed to bridge the gap between job seekers and the competitive modern hiring landscape. The system leverages large language models (LLMs) — specifically Claude AI — to provide Applicant Tracking System (ATS) compatibility scoring, targeted improvement feedback, and intelligent job role matching based solely on a candidate's resume content. Users can upload their resume in PDF format, optionally supply a job description, and receive a detailed analytical report highlighting strengths, weaknesses, and actionable recommendations. A complementary Job Role Matcher feature identifies the top five most suitable career roles for a candidate without requiring any job description input. This paper presents the motivation, system architecture, key features, technical implementation, potential applications, and future scope of the AI-Powered Interview Application Tracking System (ATS) platform.

Keywords: Resume Analysis, ATS Score, Large Language Models, Job Matching, Claude AI, NLP, Career Intelligence, Web Application.

How to Cite this Paper

Mehta, R., Rathore, R. & Sahu, N. (2026). AI-Powered Interview Application Tracking System (ATS): An AI-Powered Resume Analysis and Job Matching System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.699

Mehta, Ritika, et al.. "AI-Powered Interview Application Tracking System (ATS): An AI-Powered Resume Analysis and Job Matching System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.699.

Mehta, Ritika,Riya Rathore, and Naincy Sahu. "AI-Powered Interview Application Tracking System (ATS): An AI-Powered Resume Analysis and Job Matching System." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.699.

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References

[1] Anthropic. (2024). Claude AI — Large Language Model. https://www.anthropic.com

[2] AI-Powered Interview Application Tracking System (ATS) Project. (2024). Smart Feedback for Your Dream Job. https://resume-analyser-nine-xi.vercel.app

[3] Turcotte, B., & Feldmann, S. (2019). The Role of Applicant Tracking Systems in Modern Recruitment. Journal of Human Resources Technology.

[4] Brown, T. et al. (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems (NeurIPS).

[5] Vercel Inc. (2024). Vercel Deployment Platform. https://vercel.com

[6] Oliphant, J. (2021). Resume Parsing and Automated Screening: Opportunities and Challenges. International Journal of Recruiting Technology.

Ethical Compliance & Review Process

  • All submissions are screened under plagiarism detection.
  • Review follows editorial policy.
  • Authors retain copyright.
  • Peer Review Type: Double-Blind Peer Review
  • Published on: May 23 2026
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