 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: May 2026
Volume 11 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24205
Article Published : 9239
Total Authors : 24597
Total Reviewer : 847
Total Countries : 165
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | JobFit AI: Intelligent Resume Matching & Invigilated Examination |
| Authors Name: | Rasha Valsan , Keerthana K , Sreya Sajeevan , Gokul S , Vaishakhi V K |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_210603
|
| Published Paper Id: | IJRTI2604225 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | The modern job market presents significant challenges for candidates, including time-consuming application processes, limited personalization, and insufficient guidance for skill enhancement. Conventional job portals primarily focus on listing opportunities, requiring candidates to manually search, apply, and prepare without structured support. To overcome these limitations, the proposed system, JobFit AI: Intelligent Resume Matching & Invigilated Examination, offers a comprehensive web-based platform that automates job applications while enhancing preparation through intelligent analysis and personalized learning. Users begin by uploading their resumes in PDF or DOC formats, which are processed using Natural Language Processing (NLP) techniques to extract key information such as skills, education, experience, and certifications. This data is then matched with relevant job openings, enabling direct applications through the platform, reducing time and effort. To improve candidate readiness, the system provides aptitude and technical practice sessions, followed by detailed performance reports highlighting strengths, weaknesses, and areas for improvement. Curated video recommendations and learning resources are offered to address skill gaps, promoting continuous growth. A personalized dashboard consolidates job recommendations, application status, test scores, and improvement suggestions, facilitating progress tracking. With user consent, targeted feedback ensures efficient preparation and skill development. The platform leverages advanced Machine Learning (ML) algorithms and adaptive evaluation techniques to simulate interviews, monitor language and behavior, and analyze sentiment, preparing candidates for real-world recruitment scenarios. By integrating automation, intelligent feedback, and interactive learning, JobFit AI simplifies the job search process and equips candidates with the tools to excel in competitive environments, while simultaneously aiding recruiters in identifying well-matched talent efficiently. |
| Keywords: | Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Resume Matching, Job Recommendation System, Mock Interview, Sentiment Anal- ysis, Computer Vision. |
| Cite Article: | "JobFit AI: Intelligent Resume Matching & Invigilated Examination", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b653-b659, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604225.pdf |
| Downloads: | 000205503 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2604225
Registration ID:210603
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b653-b659 Country: Kannur, Kerala, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604225 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604225 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||