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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64335
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
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.
Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028

Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028
Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028
Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028
Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028
Information Technology
JSPM's Jayawantrao Sawant College Of Engineering Hadapsar Pune 411028
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
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.
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.
Publication Date
5/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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