Request to Add CoreRec: A Graph-Based Recommendation Engine

[vishesh9131]

Dear CoreNet Team,

I am writing to propose the addition of a new recommendation engine, CoreRec, to the CoreNet repository/technology. CoreRec is a cutting-edge recommendation engine specifically designed for graph-based algorithms. It seamlessly integrates advanced neural network architectures and excels in node recommendations, model training, and graph visualizations.

Key Features of CoreRec:

• GraphTransformer Model: A Transformer model tailored for graph data with customizable parameters.
• GraphDataset: A PyTorch dataset for efficient handling of graph data.
• Training Functionality: Comprehensive training functions for various graph-based machine learning models.
• Prediction Capability: Accurate prediction of similar nodes within a graph.
• Graph Visualization: Robust 2D and 3D graph visualization tools.

Benefits of Including CoreRec in CoreNet:

• Enhanced Recommendation Capabilities: Leverage advanced graph algorithms to improve recommendation accuracy.
• Integration with CoreNet: Seamlessly integrate CoreRec's functionalities with existing CoreNet infrastructure.
• Community Collaboration: Foster collaboration and innovation within the CoreNet community by providing a state-of-the-art recommendation engine.

Repository URL: CoreRec GitHub Repository

We believe that CoreRec would be a valuable addition to the CoreNet repository/technology and look forward to your feedback and consideration.

Thank you for your time and attention. Best regards,

Vishesh Yadav mail corerec site