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CVs Dataset
Overview
This dataset is a collection of 100 individual résumés/CVs, one file per person, stored in the CVs/ folder. It appears to be a raw batch of candidate applications (e.g. collected for a recruitment process) rather than a curated or anonymized dataset.
Contents
| Property | Value |
|---|---|
| Total files | 100 |
| PDF files | 66 |
| JPG (image) files | 34 |
| Total size | ~39 MB |
| Folder structure | Flat — all files directly inside CVs/ |
Naming Convention
Files follow the pattern:
CV_<Name>.pdf
CV_<Name>.jpg
Where <Name> is typically the candidate's first and/or last name (e.g. CV_MessaoudiYassine.pdf, CV_AncelDalila.jpg). A few files include a numeric suffix like (1) indicating a duplicate or re-submission (e.g. CV_OumriSamira.pdf and CV_OumriSamira(1).pdf).
File Formats
- PDF (66 files): Standard document-format résumés, likely exported from Word, Canva, LinkedIn, or similar tools.
- JPG (34 files): Scanned or photographed résumés, or CVs exported/screenshotted as images rather than documents.
Suggested Uses
- Input data for a résumé-parsing pipeline (OCR for JPGs, text extraction for PDFs)
- Building/testing a candidate-screening or ATS (Applicant Tracking System) tool
- Training or evaluating document-classification/extraction models — with appropriate privacy safeguards
Notes
- Since the JPG files are image scans, any automated text extraction will need OCR (e.g. Tesseract) rather than direct text parsing.
- No metadata file (e.g. CSV with candidate details, job applied for, submission date) was included alongside the CVs — only the raw files.
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