MiningResume and ResumeRise

Text extraction from resumes and classification/summarization of resumes are complementary operations—one parses structured fields while the other applies ML-based analysis to the full document—making them potential pipeline stages rather than competitors.

MiningResume
56
Established
ResumeRise
41
Emerging
Maintenance 10/25
Adoption 8/25
Maturity 16/25
Community 22/25
Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 18/25
Stars: 61
Forks: 47
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 37
Forks: 13
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: GPL-3.0
No Package No Dependents
Stale 6m No Package No Dependents

About MiningResume

yogeshhk/MiningResume

Text Mining certain fields from a resume

This project helps HR managers, recruiters, and hiring teams quickly turn stacks of resumes (PDF, Word, or text files) into organized, structured data. It extracts key information like names, contact details, skills, and work experience, providing it in an easy-to-use JSON format. This streamlines the initial screening process, making it faster to review candidates.

resume-screening recruitment HR-tech applicant-tracking candidate-sourcing

About ResumeRise

manishshettym/ResumeRise

resumerise: classify and summarizes resumes

This tool helps HR professionals, recruiters, and hiring managers efficiently sort and understand job applications. You provide a collection of resumes, and it automatically categorizes them by primary skill set and generates concise summaries for each, allowing for quicker review and ranking based on your specific job requirements. This is designed for anyone responsible for screening a large volume of candidate applications.

recruitment HR-management candidate-screening hiring talent-acquisition

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