lqj233/end-to-end_recommendation_system_x

This repository is a learning-oriented, end-to-end recommendation system. The principal path runs from the storefront’s home feed to the business API and four-stage online recommender, then returns ranked items for display and behavior tracking. Tracked events feed a documented streaming loop; batch imports and layered Spark processing supply training data, and scheduled full or incremental training produces serving artifacts. The tree omits the backend and streaming implementations, so those documented components have no source path; edges involving them rely on the README rather than sampled code.