This repository showcases the work of Kakao's Recommendation Team, focusing on advancing recommendation technologies, developing a recommendation/ML SaaS platform, and building stable, efficient platforms for large-scale recommendation services. It serves as a public resource for researchers, engineers, and anyone interested in state-of-the-art recommendation systems.

How It Works

The team's approach involves both theoretical advancements and practical platform development. They publish research on topics like periodic model updates, adversarial training, and efficient recommendation strategies. They also develop and open-source tools like TOROS (a production-ready recommender system framework) and TOROS N2 (a lightweight approximate nearest neighbor library), enabling scalable and fast recommendations even with large datasets.

Quick Start & Requirements

• Install: Specific installation commands vary by project (e.g., pip install ... for libraries).
• Prerequisites: Python, potentially specific versions of libraries like TensorFlow, and for some projects, access to large datasets or GPU resources may be beneficial.
• Resources: Setup complexity and resource needs depend on the specific tool or project within the repository.
• Links:
  • Discussions: https://github.com/kakao/recoteam/discussions
  • TOROS Buffalo: https://github.com/kakao/toros-buffalo
  • TOROS N2: https://github.com/kakao/toros-n2

Highlighted Details

• Open-sourced projects include TOROS Buffalo and TOROS N2.
• Extensive collection of published papers and presentations on recommendation systems.
• Knowledge repository with paper reviews and public documentation.
• Details on Kakao's internal recommendation system evolution and applications.

Maintenance & Community

The repository is maintained by Kakao's Recommendation Team. Community interaction is encouraged via GitHub Discussions. Links to tech blogs and past conference presentations are provided, offering insights into their work and community engagement.

Licensing & Compatibility

The specific licenses for individual projects within the repository are not uniformly stated in the README. Users should verify the license for each component (e.g., TOROS Buffalo, TOROS N2) before commercial use or integration into closed-source projects.

Limitations & Caveats

The README primarily serves as an overview and index of the team's work, rather than a direct guide to a single, runnable system. Specific project documentation should be consulted for detailed setup and usage instructions. Some projects may be research-oriented or have specific dependencies not immediately apparent.