Applicant Tracking System (ATS)

Overview

The ATS is an intelligent system designed to analyze and compare resumes against job descriptions using state-of-the-art natural language processing and mechanical matching techniques. It extracts key information, identifies similarities, and highlights gaps to streamline the hiring process.

Features

1. Soft Matches with Confidence Levels Leverages Large Language Models (LLMs) to identify textual similarities between job description keywords and resume keywords. Each match comes with a confidence level, allowing users to: Evaluate the strength of the match. Set thresholds for displaying results based on confidence levels in future iterations.

2. Keyword Extraction From Resumes: Extracts and identifies important keywords from the resume. Sorts keywords alphabetically for easy readability. From Job Descriptions: Extracts key terms from the job description. Sorts terms alphabetically for consistency and easy comparison.

3. Mechanical Matching Performs a 100% similarity match between the keywords from resumes and job descriptions. This is a case-sensitive process, ensuring matches respect upper- and lowercase distinctions. Provides a reliable list of exactly matched keywords.

4. Missing Keywords Identifies missing keywords by calculating the difference between: The extracted keywords from the job description. The mechanically matched keywords set. Highlights the gaps, giving actionable insights for resume optimization or further evaluation.

Future Enhancements

Adjustable Confidence Thresholds: Allow users to filter soft matches by confidence level. Support for Additional Document Types: Extend beyond resumes to include cover letters, investor pitches, and other structured documents. The system will incorporate advanced paragraph evaluation capabilities, allowing for a more comprehensive analysis of the text. It will identify areas of weakness, such as unclear phrasing or lack of alignment with the target context, and suggest actionable improvements to enhance overall effectiveness. Additionally, the feature will include the ability to refine bullet points or transform them into well-crafted paragraphs by incorporating specific keywords or rephrasing for greater clarity and impact. Advanced Keyword Insights: Integrate keyword importance scores to prioritize matches. Visualization Tools: Add graphical displays of match and gap analysis.

Project Structure

The project is organized into two main components:

Backend: Contains the logic for keyword extraction, soft matching, and mechanical matching. Located in the backend/ directory. Frontend: Provides a user-friendly interface for uploading resumes and job descriptions, and viewing results. Located in the root directory.

Getting Started

Prerequisites Ensure the following tools are installed:

Node.js (v14 or later) npm

Installation Clone the repository: git clone https://github.com/your-username/ats-system.git cd ats-system Install dependencies:

Backend: cd backend npm install

Frontend: cd .. npm install

Running the Project

1. Start the Backend

Navigate to the backend/ directory and start the server:

cd backend node server.js The backend will run at http://localhost:5000 by default.

2. Start the Frontend

From the root directory, start the React app:

npm start The frontend will open at http://localhost:5001 if you followed the .env.example.

Usage

Upload a resume and a job description through the interface. View the analysis: Soft Matches with confidence levels. Extracted Keywords sorted alphabetically. Mechanically Matched Keywords (100% similarity). Missing Keywords from the job description. Use the insights to refine the resume.

Contributing

We welcome contributions! Here’s how you can help:

Fork the repository. Create a feature branch: git checkout -b feature-name Commit your changes: git commit -m "Description of changes" Push the branch and create a pull request.

Technologies Used

• Frontend: React.js (JavaScript library for building user interfaces)
• Backend: Node.js (JavaScript runtime environment)
• Package Manager: npm (Node Package Manager)

License

This project is open-source and licensed under the MIT License. See the LICENSE file for details.