International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 8 Issue 1
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AI-Based Resume Shortlisting System Using NLP and Machine Learning

Author(s) Ms. Tanjila Jahangir Tamboli, Shakila Siddavatam
Country India
Abstract Recruiters and hiring managers in today’s competitive job market face major challenges in filtering thousands of resumes for a single position. Manual screening is slow, inconsistent, and often influenced by individual bias. Candidates with relevant skills are frequently overlooked due to formatting differences or keyword mismatches. As a result, both organizations and applicants experience delays, reduced productivity, and limited hiring transparency.
To address these issues, this project proposes an intelligent recruitment tool titled “AI-Based Resume Shortlisting System Using NLP and Machine Learning.” The system analyses uploaded resumes, extracts key information such as skills, education, experience, and certifications, and automatically ranks candidates based on job requirements. The platform features a recruiter dashboard for job posting and result visualization, a resume parser using Natural Language Processing (NLP), and a machine learning model that evaluates candidate-job matching scores. The system aims to support multiple file formats, multilingual resume handling, and unbiased filtering to ensure fair screening.
This research discusses the platform’s functional design, data pre-processing pipeline, NLP techniques, model selection, and evaluation metrics. By automating early-stage recruitment, the solution reduces screening time, enhances accuracy, and improves hiring decision quality for organizations of all sizes.
Keywords Keywords: Recruitment, Resume Screening, Natural Language Processing (NLP), Machine Learning, Automation, Candidate Ranking, AI Hiring System, Resume Parsing, Job Matching, HR Technology, Talent Acquisition, Shortlisting Platform
Field Computer
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-02-04
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.68093
Short DOI https://doi.org/hbnpzx
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