Thesis-Similarity-Checker-SVM-V3

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Thesis Similarity Checker SVM - Version 3

Table of Contents

1. Introduction
2. Features
3. Installation
4. Usage
5. Project Structure
6. Contributing
7. License

Introduction

Thesis Similarity Checker SVM is a tool designed to check the similarity between thesis documents using Support Vector Machines (SVM). This is the third version of the project, which includes significant improvements and new features.

Features

• High accuracy in detecting similarities between documents.
• Supports multiple document formats.
• Improved performance and scalability.
• User-friendly interface.

Installation

To install the necessary dependencies, run the following command:

pip install -r requirements.txt

Usage

To use the Thesis Similarity Checker, follow these steps:

1. Prepare your dataset.
2. Run the similarity checker script:

   python similarity_checker.py

Project Structure

The project structure is as follows:

• similarity_checker.py: Main script to run the similarity checker.
• data/: Directory containing the datasets.
• models/: Directory containing pre-trained models.
• utils/: Utility functions and helper scripts.
• tests/: Unit tests for the project.

Contributing

Contributions are welcome! Please read the CONTRIBUTING.md for guidelines on how to contribute to this project.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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