Online Resume PDF Summary System using NLP
Abstract
The Online Resume PDF Summary System aims
to streamline the recruitment process by
automating the extraction of key information
from resumes in PDF format using Natural
Language Processing (NLP) techniques. The
system is designed to analyze and summarize
resumes by identifying crucial elements such as
work experience, education, skills, and personal
details. By leveraging advanced NLP algorithms
like Named Entity Recognition (NER), part-ofspeech
tagging, and semantic analysis, the system
generates concise and accurate summaries of
resumes that are easy to review. This technology
can significantly reduce the manual effort
involved in evaluating large numbers of resumes,
improving both efficiency and accuracy for
recruiters. The proposed system will enhance the
hiring process, making it faster, more consistent,
and less prone to human error.
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References
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