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The implementation for the work "Recommender Systems with Generative Retrieval".

A collection of libraries for recommender systems

A data science system that recommends movies to users based on ratings, genres, and watch history using machine learning techniques.

A Recommendation engine for an e-commerce use case that provides recommendations to users based on their purchase history.

Search and Recommender Systems papers with Code

CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework

This is our Tensorflow implementation for "Graph-based Embedding Smoothing for Sequential Recommendation" (GES) TKDE 2021.

Recommender Systems are the systems designed to that are designed to recommend things to the user based on many different factors. These systems predict the most likely product that the users are most likely to purchase and are of interest to. Recommendations typically speed up searches and make ... Read more

A TensorFlow implementation of SOFA, the Simulator for OFfline LeArning and evaluation.

Recommendation System Using three different approaches Simple Recommendation Using Correlation, Using KNN and Collaborative Filtering.