The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

This is a repository of public data sources for Recommender Systems (RS).

A unified, comprehensive and efficient recommendation library

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

Finding relevant source domain for a cross-domain recommendation system using Unified Content-based Collaborative Filtering (CCCFNet model)

Pytorch implementation of Domain Separation Networks

Models and examples built with TensorFlow

后台面试知识

一些传统推荐算法的实现，包括基于内容的推荐，协同过滤，矩阵分解

算法思想模块总结

推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"

Graph Neural Network based Social Recommendation Model. SIGIR2019.

My blogs and code for machine learning. http://cnblogs.com/pinard

《推荐系统实践》的代码实现