Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems

Overview

DANSER-WWW-19

This repository holds the codes for Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. (WWW 2019). The requirements are Python 3.6 and Tensorflow 1.7.0.

We also release the public dataset Epinions used in our work and the trained model.

To reproduce the results in our paper, you can run

python test.py

To train the model, you can run

python train.py

and you will get similar results after about 20 epoches.

The build_dataset.py is to preprocess the dataset and outputs two .pkl files in /data. The input.py generates mini-batch samples. The eval.py contains the calculation for evaluation metrics. The model.py implements the network model proposed in our paper.

If you use this code as part of any published research, please cite the following paper:

@inproceedings{DANSER-WWW-19,
  author    = {Qitian Wu and Hengrui Zhang and Xiaofeng Gao and Peng He and
               Paul Weng and Han Gao and Guihai Chen},
  title     = {Dual Graph Attention Networks for Deep Latent Representation of Multifaceted
               Social Effects in Recommender Systems},
  booktitle = {The World Wide Web Conference, {WWW} 2019, San Francisco, CA, USA,
               May 13-17, 2019},
  year      = {2019}
  }

For more details, you can refer to our paper.

The Epinions data is provided by the work

"eTrust: Understanding trust evolution in an online world" in KDD'2012.

Owner
Qitian Wu
Qitian Wu
Implementation of a hadoop based movie recommendation system

Implementation-of-a-hadoop-based-movie-recommendation-system 通过编写代码,设计一个基于Hadoop的电影推荐系统,通过此推荐系统的编写,掌握在Hadoop平台上的文件操作,数据处理的技能。windows 10 hadoop 2.8.3 p

汝聪(Ricardo) 5 Oct 02, 2022
Hierarchical Fashion Graph Network for Personalized Outfit Recommendation, SIGIR 2020

hierarchical_fashion_graph_network This is our Tensorflow implementation for the paper: Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and

LI Xingchen 70 Dec 05, 2022
基于个性化推荐的音乐播放系统

MusicPlayer 基于个性化推荐的音乐播放系统 Hi, 这是我在大四的时候做的毕设,现如今将该项目开源。 本项目是基于Python的tkinter和pygame所著。 该项目总体来说,代码比较烂(因为当时水平很菜)。 运行的话安装几个基本库就能跑,只不过里面的数据还没有上传至Github。 先

Cedric Niu 6 Nov 19, 2022
Code for my ORSUM, ACM RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation

HeroGRAPH Code for my ORSUM @ RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation Paper, workshop pro

Qiang Cui 9 Sep 14, 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

LI, Wai Yin 90 Oct 08, 2022
Books Recommendation With Python

Books-Recommendation Business Problem During the last few decades, with the rise

Çağrı Karadeniz 7 Mar 12, 2022
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation

MKM-SR Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation Paper data and code This is the

ciecus 38 Dec 05, 2022
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021

Detecting Beneficial Feature Interactions for Recommender Systems (L0-SIGN) This is our implementation for the paper: Su, Y., Zhang, R., Erfani, S., &

26 Nov 22, 2022
E-Commerce recommender demo with real-time data and a graph database

🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str

g-despot 3 Feb 23, 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

xfl15 30 Nov 25, 2022
The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".

GCE-GNN Code This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation. Requirement

98 Dec 28, 2022
Handling Information Loss of Graph Neural Networks for Session-based Recommendation

LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro

Tianwen CHEN 62 Dec 03, 2022
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

FIB LAB, Tsinghua University 37 Dec 18, 2022
Movie Recommender System

Movie-Recommender-System Movie-Recommender-System is a web application using which a user can select his/her watched movie from list and system will r

1 Jul 14, 2022
Recommender System Papers

Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021

RUCAIBox 704 Jan 06, 2023
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
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Information Systems Lab @ Polytechnic University of Bari 215 Nov 29, 2022
Respiratory Health Recommendation System

Respiratory-Health-Recommendation-System Respiratory Health Recommendation System based on Air Quality Index Forecasts This project aims to provide pr

Abhishek Gawabde 1 Jan 29, 2022
It is a movie recommender web application which is developed using the Python.

Movie Recommendation 🍿 System Watch Tutorial for this project Source IMDB Movie 5000 Dataset Inspired from this original repository. Features Simple

Kushal Bhavsar 10 Dec 26, 2022
Collaborative variational bandwidth auto-encoder (VBAE) for recommender systems.

Collaborative Variational Bandwidth Auto-encoder The codes are associated with the following paper: Collaborative Variational Bandwidth Auto-encoder f

Yaochen Zhu 14 Dec 11, 2022