ICDM-2020 《Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks》
dataprocess:
python dataProcess.py --dataset [CiaoDVD,Epinions,Douban] --rate [0.8,0.6]
train SR-HGNN model:
python main.py --dataset CiaoDVD --rate 0.8 --batch 128 --lr 0.001 --layer [16,16] --r 0.001 --r2 0.2 --r3 0.01 --dgi_hide_dim 500 --dgi_lr 0.001 --lam_t 0.05 --lam_r 0.1
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
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Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021
Book Recommendation System A recommendation system for suggesting new books given similar books. Datasets Dataset Kaggle Dataset Notebooks goodreads-E
(中文文档|简体中文|English) 什么是推荐系统? 推荐系统是在互联网信息爆炸式增长的时代背景下，帮助用户高效获得感兴趣信息的关键； 推荐系统也是帮助产品最大限度吸引用户、留存用户、增加用户粘性、提高用户转化率的银弹。 有无数优秀的产品依靠用户可感知的推荐系统建立了良好的口碑，也有无数的公司依
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
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
KHGT Code for KHGT accepted by AAAI2021 Please unzip the data files in Datasets/ first. To run KHGT on Yelp data, use python labcode_yelp.py For Movi
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
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
Books-Recommendation Business Problem During the last few decades, with the rise
Collaborative Variational Bandwidth Auto-encoder The codes are associated with the following paper: Collaborative Variational Bandwidth Auto-encoder f
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.
Bi-TGCF Tensorflow Implementation of BiTGCF： Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20
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
Temporal Meta-path Guided Explainable Recommendation (WSDM2021) TMER Code of paper "Temporal Meta-path Guided Explainable Recommendation". Requirement
Recommendation-Systems-for-IBM-Watson-Studio-platform Project Overview In this project, I analyze the interactions that users have with articles on th
SGL This is our Tensorflow implementation for our SIGIR 2021 paper: Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian,and Xing
DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph
Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with th
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