asoyewole/skeegap

Project Skee Gap

Resume-to-Job Skill Matcher

A resume and job description skill extraction and matching tool that leverages Natural Language Processing (NLP), Sentence Transformers, and fuzzy matching to help candidates and recruiters quickly identify how well a resume aligns with a given job description.

This project provides a Streamlit-based web application where users can:

1. 1.Upload or paste a resume (.pdf, txt, or .docx)

1. 1.Upload or Paste a job description

1. 1.Extract and match skills against a skills knowledge base (skills.csv)

1. 1.View expandable sections of Matched Skills and Missing Skills

1. 1.Gain insights into resume-job fit in an interactive and user-friendly manner

🔑 Key Features

1. 1.Skill Extraction from Resume: Uses spaCy and regex rules to extract relevant skills from the resume text.

1. 1.Job Description Skill Extraction: Identifies required skills from the job description using NLP and similarity scoring.

1. 1.Fuzzy Matching with Skills Dataset: Even if the exact skill wording differs, fuzzy string matching ensures relevant skills are captured (e.g., “PyTorch” vs. “Torch”).

1. 1.Sentence Transformer Embeddings: Improves semantic matching of skills by comparing embeddings rather than just keywords.

1. 1.Expandable Matched/Missing Skills Panels: Avoids screen clutter by hiding detailed lists until the user chooses to expand them.

1. 1.Interactive Streamlit App: Clean, user-friendly interface to upload resumes, paste job descriptions, and instantly view results.

📂 Project Structure resume-skill-matcher/ │ ├── app.py # Streamlit main app ├── extractskills.py # Skill extraction + fuzzy/semantic matching logic ├── skills.csv # Master skills dataset (expandable/customizable) ├── requirements.txt # Project dependencies ├── README.md # Documentation (this file) └── sampleresumes/ # (Optional) Example resumes for testing ├── scores.py # compute the scores, compares └── extract_text.py # Extract text from resume and job desc.

🏗️ Architecture Overview flowchart TD A[User Uploads Resume] -->|PDF/DOCX Parsing| B[Resume Text Extraction] C[User Pastes Job Description] --> D[Job Description Text Extraction]

B --> E[Skill Extraction via spaCy + Regex] D --> F[Skill Extraction via spaCy + Regex]

E --> G[Fuzzy Matching with skills.csv] F --> G

G --> H[Sentence Transformer Embeddings for Semantic Similarity] H --> I[Matched Skills / Missing Skills Classification]

I --> J[Streamlit Expandable Panels]

🧩 Skills Dataset (skills.csv) The skills dataset use in the project is from Skill2vec (2017).

@article{van2017skill2vec, title={Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job Description}, author={Van-Duyet, Le and Quan, Vo Minh and An, Dang Quang}, journal={arXiv preprint arXiv:1707.09751}, year={2017} }

The file skills.csv contains the reference set of skills used for matching. You can customize it for different industries.

Example structure:

skill Python SQL Data Analysis Machine Learning Deep Learning Project Management Docker AWS

You can expand this dataset to cover domain-specific skill sets (e.g., finance, healthcare, cybersecurity).

📊 Example Workflow

Upload resume.pdf

Paste job description into the app

Click Analyze

View results:

✅ Matched Skills (expandable list)

❌ Missing Skills (expandable list)

Use insights to improve your resume or assess candidate fit.

🚀 Roadmap / Future Enhancements

Add resume scoring system (percentage match score)

Generate recommendations for missing skills

Extend support for multi-page resumes and multiple job postings

Add export to PDF/Excel feature for results

Enhance semantic similarity using large language models (LLMs)

Integrate with LinkedIn or job boards for automatic skill extraction

📜 License

This project is licensed under the MIT License.

🙌 Acknowledgments

spaCy for NLP pipelines

Sentence Transformers for semantic similarity

RapidFuzz for efficient fuzzy string matching

Streamlit for building the interactive web app

@article{van2017skill2vec, title={Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job Description}, author={Van-Duyet, Le and Quan, Vo Minh and An, Dang Quang}, journal={arXiv preprint arXiv:1707.09751}, year={2017} }