Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM64335

Smart Resume Screening Web Application

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64335

Volume:

10 |

5 |

May 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

Ishwar Dattatray Kirave

Ishwar Dattatray Kirave

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Author Certificate
Ritesh Anil Kanse

Ritesh Anil Kanse

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Co-Author Certificate
OVM

Om Vijay Mhatre

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Co-Author Certificate
PVS

Puja Vijay Suralkar

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Co-Author Certificate
JJL

Jay Jagdish Lad

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Co-Author Certificate

Mentors

PMG

Prof. Manisha Gade

Information Technology

JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Download Mentor Certificate

Author Services & Downloads

Full ArticlesAcceptance Certificate

Abstract

The recruitment process often requires screening a large number of resumes, making candidate selection time-consuming and prone to human bias. This paper presents ResumeIQ, a Smart Resume Screening Web Application designed to automate resume analysis and candidate ranking using Artificial Intelligence (AI) and Natural Language Processing (NLP). The proposed system provides separate modules for students and recruiters. Students can evaluate their resumes through an ATS simulation system, identify missing skills, and receive improvement suggestions, while recruiters can upload job descriptions and multiple resumes for automated screening. The system extracts candidate information, performs keyword and semantic similarity matching, and generates ranking scores based on job relevance. Additional features such as skill-gap analysis, candidate comparison, analytics dashboards, and report generation enhance the recruitment process. Experimental results demonstrate that the system significantly reduces screening time, improves candidate-job matching accuracy, and provides actionable insights for both recruiters and job seekers. The proposed solution offers an efficient, scalable, and user-friendly approach to modern recruitment and resume evaluation.

KEYWORDS

Artificial Intelligence Natural Language Processing Resume Screening ATS Candidate Ranking Recruitment Automation

Cite This Article

Ishwar Dattatray Kirave, Ritesh Anil Kanse, Om Vijay Mhatre, Puja Vijay Suralkar, Jay Jagdish Lad, Prof. Manisha Gade, "Smart Resume Screening Web Application," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-5, May 2026.

Full Article/Conclusion

The ResumeIQ: Smart Resume Screening Web Application demonstrates the effective use of Artificial Intelligence (AI) and Natural Language Processing (NLP) in automating resume evaluation and candidate selection. The system simplifies the recruitment process by performing resume parsing, ATS scoring, candidate ranking, and skill-gap analysis. The proposed solution benefits both recruiters and job seekers by reducing manual effort, improving screening accuracy, and providing valuable feedback for resume improvement. Experimental results show that the system enables faster candidate shortlisting and more efficient hiring decisions. In conclusion, ResumeIQ provides an intelligent, user-friendly, and scalable approach to recruitment automation. Future enhancements may include advanced AI models, improved semantic analysis, and cloud-based deployment for large-scale applications.

References

1. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT, 4171–4186.   2. Reimers, N., & Gurevych, I. (2019). Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. Proceedings of EMNLP-IJCNLP, 3982–3992.   3. Kumar, M., Sharma, A., & Singh, P. (2020). Resume Ranking System using TF-IDF and Cosine Similarity for Recruitment Automation. International Journal of Computer Applications, 176(25), 15–20.   4. Smart Hiring System using Artificial Intelligence. International Journal of Engineering Research & Technology (IJERT), 2022.    

Editorial & Review Transparency

Publication Date

5/30/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

3

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...