🌌 Kori

Kori is an anime recommendation system written in Python, built using the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm.

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📁 Project Structure

• /src: Main source code of the recommendation system (all core logic and modules)
• /docs: Project documentation (including LaTeX files and generated PDFs)

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✨ Features

• Recommends anime titles based on user input and content similarity
• Utilizes TF-IDF for text vectorization and similarity calculation
• Integrated search system using external APIs for up-to-date anime information
• Allows users to view episodes info of the selected anime
• Modular and extensible codebase
• Easy to use and adapt for other recommendation tasks

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🧑‍💻 Technologies

• Httpx
• NLTK
• Numpy
• Pandas

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📚 How It Works

1. The system processes a dataset of anime descriptions.
2. Each description is transformed into a TF-IDF vector.
3. When a user search and selects an anime, the system calculates the similarity between the query and all anime in the dataset.
4. The most similar anime are recommended to the user.

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🏫 Academic Context

This project was created for the Linear Algebra course at FATEC Rubens Lara. It demonstrates the application of vector spaces and similarity measures in real-world problems.

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🚀 Getting Started

1. Clone this repository
2. Install dependencies (see pyproject.toml)
3. Run main.py to start the recommendation system

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📄 License

This project is for academic purposes.