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adpr

ADPR: An Attention-based Deep Learning Point-of-Interest Recommendation Framework

an-attention-based-spatiotemporal-lstm-network-for-next-poi-recommendation

A python vision code of An Attention-based Spatiotemporal LSTM Network for Next POI Recommendation

apoir

Adversarial Point-of-Interest Recommendation

bootstrap5-bootcamp

cape

In this repository, We're going to implement the paper, which is "Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation", (B. Chang et al, IJCAI-ECAI'18), using a PyTorch library.

cheatsheets

Official Matplotlib cheat sheets

code_snippets

collaborative_deep_learning

Collaborative Deep Learning (CDL)

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deeprecommender

Deep learning for recommender systems

diffnet

distance2pre

Code for my PAKDD-2019, Distance2Pre: Personalized Spatial Preference for Next Point-of-Interest Prediction

gae

Implementation of Graph Auto-Encoders in TensorFlow

gate

The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"

gcn-recsys

A Graph Convolution Network based approach to Recommender Systems

geom-gcn

Geom-GCN: Geometric Graph Convolutional Networks

gnn-benchmark

Framework for evaluating Graph Neural Network models on semi-supervised node classification task

goru-tensorflow

Gated Orthogonal Recurrent Unit implementation in tensorflow

graph-based-recommendation-system

Graph convolutional matrix completion

graph-cnn-recommender-systems

graph-embeddings-for-recommender-systems

In this project, we will revisit the problem central to recommender systems: predicting a user’s preference for some item they have not yet rated. Like the Spark recommender from the first project, we will use a collaborative filtering model to explore this problem. Recall that in this model, the goal is to find the sentiment of a user about a particular item Unlike the the first project that used the ALS method, however, we will perform this task using a graphbased technique called DeepWalk.

graph-lstm

graph_nets

PyTorch Implementation and Explanation of Graph Representation Learning papers involving DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

graphrec-www19

Graph Neural Networks for Social Recommendation, WWW'19

graphsage

Representation learning on large graphs using stochastic graph convolutions.

gru4rec

GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Networks with Top-k Gains for Session-based Recommendations". The code is optimized for execution on the GPU.

hamoye-classes

hgn

Hierarchical Gating Networks for Sequential Recommendation

igmc

Inductive graph-based matrix completion (IGMC) from "M. Zhang and Y. Chen, Inductive Matrix Completion Based on Graph Neural Networks, ICLR 2020 spotlight".

knowledge_graph_attention_network

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019