Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{192700,
        author = {Ishwar Dattatray Kirave and Ritesh Anil Kanse and Jay Jagdish Lad and Om Vijay Mhatre and Puja Vijay Suralkar},
        title = {SRS-WA:Smart Resume Screening Web Application},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {4710-4714},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192700},
        abstract = {The recruitment process often involves screening a large number of resumes to identify candidates who best match a job’s requirements. Manual resume screening is time-consuming, error-prone, and subjective. To overcome these challenges, this project proposes a Smart Resume Screening Web Application that automates the evaluation and ranking of resumes using artificial intelligence and natural language processing (NLP) techniques.
The system allows recruiters to upload job descriptions and candidate resumes in various formats (PDF/DOCX). It then extracts relevant information such as skills, education, experience, and certifications from each resume using NLP-based text parsing. The extracted data is compared with the job requirements, and a matching score is generated for each candidate based on skills similarity, experience relevance, and keyword matching.
The web interface presents recruiters with a ranked list of candidates, highlighting key matches and enabling efficient shortlisting. This intelligent automation significantly reduces screening time, improves accuracy, and ensures fair candidate evaluation.
Overall, the Smart Resume Screening Web Application enhances the hiring process by combining data extraction, semantic analysis, and web-based interactivity into a unified, efficient recruitment tool.},
        keywords = {},
        month = {February},
        }