An Intelligent Web Platform for Job Search and Skill Matching Using Smart Filtering Techniques

Sanabam Bineshwor Singh; T. Abhishek; T. Manikanta; K. Hima Bindhu; Vishal Dev Kumar

doi:10.55524/ijirem.2026.13.2.6

Abstract

Recruitment is now widely conducted using online recruitment platforms. However, most of the online recruitment platforms currently in use only provide simple keyword matching between resumes and job descriptions. This does not capture the true meaning of the skills and experience possessed by the candidates and can often provide inaccurate job recommendations and increased processing for the recruiters. In this paper, an intelligent web-based job search and skill matching system using Natural Language Processing (NLP) techniques for more accurate candidate and job matching is proposed. The proposed system uses the spaCy library for information retrieval from resumes and the Sentence Transformers library for semantic similarity between the candidate and job descriptions. In addition, the DistilBERT model is utilized for the contextual classification of the jobs. The system is built using the Django framework for the backend and React for the frontend. The system implemented a hybrid approach using the TF-IDF model as a fallback option in the event of unavailability of embedding services. The experimental results show that the semantic similarity-based matching provides more accurate job recommendations than the simple keyword matching approach with an accuracy of 87%. The method may find applications in real time job search.

Keywords

Natural Language Processing; Semantic Skill Matching; Resume Parsing; Recruitment Automation; Trans- former Models; Intelligent Job Recommendation System.

References

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Cites this article as

S. B. Singh, T. Abhishek, T. Manikanta, K. H. Bindhu, V. D. Kumar, "An Intelligent Web Platform for Job Search and Skill Matching Using Smart Filtering Techniques", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-13, Issue-2, Page No-38-46, 2026. Available from: https://doi.org/10.55524/ijirem.2026.13.2.6

Corresponding Author

Sanabam Bineshwor Singh

Department of Computer Science & Engineering (AI & ML), Malla Reddy University, Hyderabad, India

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