RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

Last update: Dec 28, 2022

Related tags

Overview

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

Pytorch based implemention of Relational Temporal Attentive Graph NeuralNetworks for recommender systems, based on our paper:

Cheng HSU, Cheng-Te Li, Relational Temporal Attentive Graph NeuralNetworks (2021)

Requirements

Python 3.6
Pytorch (1.4)

Usage

To reproduce the experiments mentioned in the paper you can run the following command:

python train.py

Note: .

Cite

Please cite our paper if you use this code in your own work:

@article{vdberg2021graph,
  title={RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendationn},
  author={Cheng Hsu and Cheng-Te Li},
  journal={arXiv preprint arXiv:2101.12457},
  year={2021}
}

Owner

GitHub Repository

Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks

SR-HGNN ICDM-2020 《Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks》 Environments python 3.8 pytorch-1.6 DGL 0.5.

9 Nov 12, 2022

A Python implementation of LightFM, a hybrid recommendation algorithm.

LightFM Build status Linux OSX (OpenMP disabled) Windows (OpenMP disabled) LightFM is a Python implementation of a number of popular recommendation al

4.2k Jan 02, 2023

Graph Neural Network based Social Recommendation Model. SIGIR2019.

Basic Information: This code is released for the papers: Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Dif

144 Dec 29, 2022

Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch

Recommendation engines are one of the most well known, widely used and highest value use cases for applying machine learning. Despite this, while there are many resources available for the basics of

793 Dec 18, 2022

Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction

MGNN-SPred This is our Tensorflow implementation for the paper: WenWang,Wei Zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, and Hongyuan Zha. 2020. Bey

18 Jan 02, 2023

The official implementation of "DGCN: Diversified Recommendation with Graph Convolutional Networks" (WWW '21)

DGCN This is the official implementation of our WWW'21 paper: Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li, DGCN: Diversified Recommendation wi

37 Dec 18, 2022

Bundle Graph Convolutional Network

Bundle Graph Convolutional Network This is our Pytorch implementation for the paper: Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin and Yong Li. Bun

55 Dec 25, 2022

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and newly state-of-the-art recommendation models are implemented.

1.4k Dec 27, 2022

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation Pytorch based implemention of Relational Temporal

28 Dec 28, 2022

A Library for Field-aware Factorization Machines

Table of Contents ================= - What is LIBFFM - Overfitting and Early Stopping - Installation - Data Format - Command Line Usage - Examples -

1.6k Dec 05, 2022

Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions

Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions This repository contains the code of the paper "Accuracy-Diversity Trade-of

2 Sep 16, 2022

Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks

Bi-TGCF Tensorflow Implementation of BiTGCF： Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20

17 Nov 30, 2022

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embeddi

90 Oct 08, 2022

A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".

This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp

30 Nov 25, 2022

NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs.

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in

420 Jan 04, 2023

EXEMPLO DE SISTEMA ESPECIALISTA PARA RECOMENDAR SERIADOS EM PYTHON

exemplo-de-sistema-especialista EXEMPLO DE SISTEMA ESPECIALISTA PARA RECOMENDAR SERIADOS EM PYTHON Resumo O objetivo de auxiliar o usuário na escolha

3 Aug 31, 2021

A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (WSDM 2021)

FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (

31 Jan 04, 2023

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

Related tags

Overview

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

Requirements

Usage

Cite

Owner

Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks

A Python implementation of LightFM, a hybrid recommendation algorithm.

Graph Neural Network based Social Recommendation Model. SIGIR2019.

Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch

Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction

The official implementation of "DGCN: Diversified Recommendation with Graph Convolutional Networks" (WWW '21)

Bundle Graph Convolutional Network

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation

A Library for Field-aware Factorization Machines

Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions

Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms

A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".

NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs.

EXEMPLO DE SISTEMA ESPECIALISTA PARA RECOMENDAR SERIADOS EM PYTHON

A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (WSDM 2021)

This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)

Attentive Social Recommendation: Towards User And Item Diversities

Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"