Awesome GitHub RepositoriesGreedy Re-Ranking Algorithms

fun-rec is a learning guide and framework for building personalized recommendation systems, covering everything from deep learning ranking to generative recommendation paradigms. It provides instructional content on constructing industrial-grade architectures that span offline data processing and real-time online serving. The project distinguishes itself by focusing on generative recommendation, treating the suggestion process as a sequence-to-sequence task using large language models and transformer models to generate item identifiers rather than traditional ranking lists. It also emphasizes

This project is a neural recommendation system framework designed for building industrial-scale suggestion engines. It functions as a machine learning pipeline that implements candidate retrieval and multi-stage ranking models to suggest relevant items based on user behavior and preferences. The framework utilizes a dual-tower retrieval engine to embed users and items into a shared vector space for fast similarity searches. It incorporates a recommendation diversity controller and a re-ranking mechanism to penalize redundancy, while a sequential user behavior model processes chronological act