Resume Screening and Recommendation System Using Machine Learning Approaches

Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-15
DOI
https://doi.org/10.5281/zenodo.17356679
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Resume Screening and Recommendation System Using Machine Learning Approaches

Zenodo (CERN European Organization for Nuclear Research)
Recommender Systems and Techniques
article

Resume Screening and Recommendation System Using Machine Learning Approaches

article en

Abstract

Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.

Zenodo (CERN European Organization for Nuclear Research)
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Recommender Systems and Techniques
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