[ICDMW 2020] Code and dataset for "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation"

Overview

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation

This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ ICDM) paper: DGTN: Dual-channel Graph Transition Network for Session-based Recommendation. Please check our paper for more details about our work if you are interested.

Usage

Following the steps below to run our codes:

1. Preprocess

The preprocess code is in preprocess/

2. Neighbors retrieval

Please run neigh_retrieval/neighborhood_retrieval.py

3. Run the model

Please run main.py

Requirements

  • Python 3
  • PyTorch 1.1.0

Citation

If you find this repo is useful for you, please kindly cite our paper.

@inproceedings{zheng2020dgtn,
    title={DGTN: Dual-channel Graph Transition Network for Session-based Recommendation},
    author={Zheng, Yujia and Liu, Siyi and Li, Zekun and Wu, Shu},
    booktitle={ICDMW},
    year={2020},
}
Owner
Yujia
Yujia
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
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
The implementation of the submitted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.

DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph

10 Jul 12, 2022
Bert4rec for news Recommendation

News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation

saran pandian 2 Feb 04, 2022
Group-Buying Recommendation for Social E-Commerce

Group-Buying Recommendation for Social E-Commerce This is the official implementation of the paper Group-Buying Recommendation for Social E-Commerce (

Jun Zhang 37 Nov 28, 2022
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.

xhc 9 Nov 12, 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

Wen Wang 18 Jan 02, 2023
Code for MB-GMN, SIGIR 2021

MB-GMN Code for MB-GMN, SIGIR 2021 For Beibei data, run python .\labcode.py For Tmall data, run python .\labcode.py --data tmall --rank 2 For IJCAI

32 Dec 04, 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
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021

FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende

lei 39 Oct 26, 2022
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

PeijieSun 144 Dec 29, 2022
Recommender systems are the systems that are designed to recommend things to the user based on many different factors

Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filte

Happy N. Monday 3 Feb 15, 2022
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

Spotify 10.6k Jan 01, 2023
Attentive Social Recommendation: Towards User And Item Diversities

ASR This is a Tensorflow implementation of the paper: Attentive Social Recommendation: Towards User And Item Diversities Preprint, https://arxiv.org/a

Dongsheng Luo 1 Nov 14, 2021
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
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
Recommender System Papers

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

RUCAIBox 704 Jan 06, 2023
A framework for large scale recommendation algorithms.

A framework for large scale recommendation algorithms.

Alibaba Group - PAI 880 Jan 03, 2023
Fast Python Collaborative Filtering for Implicit Feedback Datasets

Implicit Fast Python Collaborative Filtering for Implicit Datasets. This project provides fast Python implementations of several different popular rec

Ben Frederickson 3k Dec 31, 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