International Journal For Multidisciplinary Research

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

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 2
March-April 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Enhancing Recruitment Efficiency Through AI-Driven Resume Screening and Skill Assessment

Author(s) Dr. Amrita Sarkar, Mr. Sahil Sharma, Mr. Himanshu Himanshu, Mr. Anurag Dey Sarkar, Mr. Aditya Kumar
Country India
Abstract A typical recruitment process in an organization is considered a time-consuming process since many manual steps are involved. Besides this, there also exist biases leading them toward inefficiencies, causing bad candidate-job matches. The present paper articulates the design of Revit-an AI recruitment platform pursuing automation in candidate evaluation and enhancement thereof by NLP and ML techniques. Revit provides a two-step evaluation framework: resume screening using semantic similarity analysis and an auto-generated domain-specific quiz for testing technical skills. The system uses some functionality from spaCy and sentence-transformers, as well as Firebase infrastructure, in order to formalize hiring workflows, minimize human-in-loop decisions, and aid in making data-driven decisions. An empirical evaluation on a data set containing 500 resumes and 50 job postings showed that the system could match candidates against jobs with a 95% accuracy and reduce screening time by 70%. Thus, proving that AI can enhance recruitment processes to achieve scalability, fairness, and transparency.
Keywords AI Recruitment, Resume Screening, Semantic Similarity, Natural Language Processing (NLP), Technical Skill Assessment
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-08-01
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.52621
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 1Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals