What question did this study set out to answer?

The aim is to develop a system that automates candidate screening by ranking resumes according to their relevance to job descriptions.

April 21, 2026Open Access

AI Resume Ranker using Deep Learning

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Automated system ranks resumes based on job description relevance, improving recruitment efficiency.

The aim is to develop a system that automates candidate screening by ranking resumes according to their relevance to job descriptions.
Utilizes natural language processing (NLP) for text preprocessing including tokenization and normalization.
Applies deep learning models like LSTM, BiLSTM, and CNN that analyze the semantic similarity of resumes to job descriptions.
Generates a ranked list of candidates based on computed relevance scores.
The system significantly reduces manual effort in candidate selection.
It improves accuracy and minimizes bias in identifying suitable applicants.
The ranked output facilitates faster decision-making for recruiters.

Vardhan et al. (2026) studied this question.

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