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
A general purpose recommender metrics library for fair evaluation.
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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 Gr
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Explainable Mutual Fund Recommendation Data Please see 'DATA_DESCRIPTION.md' for mode detail. Recommender System Methods Baseline Collabarative Fiilte
SEFrame This repository contains the code for the paper "An Efficient and Effective Framework for Session-based Social Recommendation". Requirements P
A framework for large scale recommendation algorithms.
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recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als
Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021
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