This project aims to implement a document classification system using graph theory principles. By representing documents as graphs and leveraging graph-based features, the system can categorize documents into predefined topics with improved accuracy compared to traditional vector-based models.
To install and set up the project, follow these steps:
- Clone the repository to your local machine.
- Representation of documents as directed graphs.
- Extraction of graph-based features using common subgraph identification techniques.
- Classification of documents using the K-Nearest Neighbors (KNN) algorithm based on graph similarity measures.
Contributions to the project are welcome! If you'd like to contribute:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them with clear messages.
- Push your changes to your fork.
- Submit a pull request, clearly describing the changes implemented.
This project is licensed under the MIT License.
Sir Waqas Ali
For any inquiries or feedback, please contact: