Thesis Similarity Checker SVM V2

This repository contains a project for checking the similarity of thesis documents using Support Vector Machine (SVM) models. The project is designed to assist in identifying and analyzing similarities between academic theses.

Features

• SVM-based Similarity Checking: Utilizes Support Vector Machine models to perform document similarity checks.
• Document Preprocessing: Includes functions for text preprocessing such as tokenization, stemming, and stop-word removal.
• Similarity Metrics: Implements various similarity metrics to evaluate the similarity between documents.
• Extensive Testing: Contains unit tests to ensure the accuracy and reliability of the similarity checking process.

Installation

To install and set up the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/delosreyesjohnpaul/Thesis-Similarity-Checker-SVM-V2.git
   cd Thesis-Similarity-Checker-SVM-V2

2. Set up a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

Usage

To use the similarity checker, you can run the main script with your documents as input. Example usage:

python main.py --input1 document1.txt --input2 document2.txt