Resume Shortlisting System [NLP and ML]

This project is inspired by the paper "Hiring and Recruitment Process Using Machine Learning" and aims to automate and optimize the resume screening process. It applies natural language processing (NLP) and machine learning techniques to evaluate and rank job candidates based on their resumes.

---

📌 Project Overview

Recruiters often face challenges in manually screening and ranking a large number of resumes. This system provides an ML-based solution to:

• Extract relevant skills and qualifications from resumes
• Match them with job role requirements
• Rank candidates based on proficiency and certification
• Output results in a structured format to aid HR decision-making

---

🧠 Core Features

• Resume parsing and keyword matching
• Skill evaluation using TF-IDF (Term Frequency-Inverse Document Frequency)
• Candidate ranking based on skill match and course completion
• Output of ranked candidates in Excel/CSV format
• Visualization of results using Matplotlib

---

🛠️ Tools & Technologies

• Language: Python
• Libraries: Pandas, Scikit-learn, Matplotlib, NLTK, SpaCy, NumPy
• Environment: Jupyter Notebook
• Data Formats: .txt, .csv, .xlsx (resumes or structured inputs)

---

⚙️ How It Works

1. Input Stage:

   • Candidates upload their resume (PDF or text)
   • System checks for keywords related to required skills (e.g., "machine learning", "Python")

2. Preprocessing:

   • NLP is used to extract text and clean it
   • TF-IDF is applied to identify key skills and courses mentioned

3. Ranking Algorithm:

   • Assigns scores based on skill match, experience, and coursework
   • Candidates are sorted based on total scores

4. Output:

   • Ranks displayed in Excel format
   • Graphs showing distribution of skills and ranking insights

---

📊 Example Visual Output

• Bar chart of top 10 ranked candidates
• Pie chart of common skills
• Line chart comparing experience vs. score

---

🚀 Future Improvements

• Resume upload via web interface (Flask/Streamlit)
• Integration with LinkedIn APIs for profile evaluation
• Deep learning for contextual understanding
• Bias and fairness evaluation in ranking

---

📚 Reference

Paper: Hiring and Recruitment Process Using Machine Learning
IEEE Xplore - Dahlia Sam et al., 2023

---

👨‍💻 Author

Shaik Abdullah
Connect with me on LinkedIn
Explore more projects on GitHub