Price-aware Recommendation with Graph Convolutional Networks,

Overview

PUP

This is the official implementation of our ICDE'20 paper:

Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin, Price-aware Recommendation with Graph Convolutional Networks, In Proceedings of IEEE ICDE 2020.


First download the Yelp dataset (link) and the category file (link).

Then generate training data and test data using the codes in src/yelp_restaurant_pipeline:

python generate_action_log.py
python generate_bridge.py
python generate_training_data_sample_fm_bpr.py

Then start the visdom server:

visdom -port 33332

Then simply run the following command to reproduce the experiments:

python app.py --flagfile ./config/yelp.cfg

If you use our codes and datasets in your research, please cite:

@inproceedings{zheng2020price,
  title={Price-aware recommendation with graph convolutional networks},
  author={Zheng, Yu and Gao, Chen and He, Xiangnan and Li, Yong and Jin, Depeng},
  booktitle={2020 IEEE 36th International Conference on Data Engineering (ICDE)},
  pages={133--144},
  year={2020},
  organization={IEEE}
}
Owner
S4rawBer2y
Keep curious, keep thinking.
S4rawBer2y
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
fastFM: A Library for Factorization Machines

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

1k Dec 24, 2022
[ICDMW 2020] Code and dataset for "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation"

DGTN: Dual-channel Graph Transition Network for Session-based Recommendation This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ I

Yujia 25 Nov 17, 2022
Books Recommendation With Python

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

Çağrı Karadeniz 7 Mar 12, 2022
Spark-movie-lens - An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset

A scalable on-line movie recommender using Spark and Flask This Apache Spark tutorial will guide you step-by-step into how to use the MovieLens datase

Jose A Dianes 794 Dec 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
This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)

GHCF This is our implementation of the paper: Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu and Shaoping Ma. 2

Chong Chen 53 Dec 05, 2022
Bert4rec for news Recommendation

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

saran pandian 2 Feb 04, 2022
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
6002project-rl - An implemention of offline RL on recommender system

An implemention of offline RL on recommender system @author: misajie @update: 20

Tzay Lee 3 May 24, 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
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.

RecList is an open source library providing behavioral, "black-box" testing for recommender systems.

Jacopo Tagliabue 375 Dec 30, 2022
A movie recommender which recommends the movies belonging to the genre that user has liked the most.

Content-Based-Movie-Recommender-System This model relies on the similarity of the items being recommended. (I have used Pandas and Numpy. However othe

Srinivasan K 0 Mar 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
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
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
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation

Reinforcement Knowledge Graph Reasoning for Explainable Recommendation This repository contains the source code of the SIGIR 2019 paper "Reinforcement

Yikun Xian 197 Dec 28, 2022
A library of metrics for evaluating recommender systems

recmetrics A python library of evalulation metrics and diagnostic tools for recommender systems. **This library is activly maintained. My goal is to c

Claire Longo 458 Jan 06, 2023
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
Real time recommendation playground

concierge A continuous learning collaborative filter1 deployed with a light web server2. Distributed updates are live (real time pubsub + delta traini

Mark Essel 16 Nov 07, 2022