IJSMT Journal

International Journal of Science, Strategic Management and Technology

An International, Peer-Reviewed, Open Access Scholarly Journal Indexed in recognized academic databases · DOI via Crossref The journal adheres to established scholarly publishing, peer-review, and research ethics guidelines set by the UGC

ISSN: 3108-1762 (Online)
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AI RESUME SCREENING + JOB RECOMMENDATION SYSTEM + RESUME BUILDER

AUTHORS:
Omkar Nilesh Biradar
Ruturaj Ravindra Patil
Om Shivaji Phadatare
Vidyasagar Murhari Thakare
Mentor
Affiliation
Kj’s Trinity Polytechnic, Pune, India
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

The rapid growth of job applications in the digital era has made the recruitment process time-consuming and inefficient when handled manually. This project presents an AI Resume Screening + Job Recommendation System + Resume Builder, an intelligent solution designed to automate and enhance the hiring process using advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP).


The system analyzes resumes by extracting key information such as skills, education, and work experience, and matches them with job descriptions using techniques like TF-IDF and cosine similarity. Based on this analysis, it ranks candidates according to their suitability for specific roles. Additionally, the system includes a job recommendation module that suggests relevant job opportunities tailored to the user’s profile and preferences.

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Biradar, O. N., Patil, R. R., Phadatare, O. S. & Thakare, V. M. (2026). AI Resume Screening + Job Recommendation System + Resume Builder. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.195

Biradar, Omkar, et al.. "AI Resume Screening + Job Recommendation System + Resume Builder." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.195.

Biradar, Omkar,Ruturaj Patil,Om Phadatare, and Vidyasagar Thakare. "AI Resume Screening + Job Recommendation System + Resume Builder." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.195.

References
1.Joachims, “Text Categorization with Support Vector Machines: Learning with Many Relevant Features,” European Conference on Machine Learning, 1998.

2.D. Manning, P. Raghavan, and H. Schütze, “Introduction to Information Retrieval,” Cambridge University Press, 2008.

3.P. Murphy, “Machine Learning: A Probabilistic Perspective,” MIT Press, 2012.

4.Bird, E. Klein, and E. Loper, “Natural Language Processing with Python,” O’Reilly Media, 2009.

5.Salton and M. McGill, “Introduction to Modern Information Retrieval,” McGraw-Hill, 1983.

6.Han, M. Kamber, and J. Pei, “Data Mining: Concepts and Techniques,” Morgan Kaufmann, 2011.

7.A Géron, “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow,” O’Reilly Media, 2019.

F. Pedregosa et
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✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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