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 data, run
python .\labcode_samp.py --data ijcai --rank 2 --graphSampleN 40000
Code for MB-GMN, SIGIR 2021
Overview
Graph Neural Network based Social Recommendation Model. SIGIR2019.
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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".
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Recommender System Papers
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704 Jan 06, 2023
Self-supervised Graph Learning for Recommendation
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
151 Dec 20, 2022
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
Mutual Fund Recommender System. Tailor for fund transactions.
Explainable Mutual Fund Recommendation Data Please see 'DATA_DESCRIPTION.md' for mode detail. Recommender System Methods Baseline Collabarative Fiilte
2 May 19, 2022
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a power
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Graph Neural Networks for Recommender Systems
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217 Jan 04, 2023
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
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A library of Recommender Systems
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Spark-movie-lens - An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset
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794 Dec 23, 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
0 Mar 31, 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
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Deep recommender models using PyTorch.
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin
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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
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An open source movie recommendation WebApp build by movie buffs and mathematicians that uses cosine similarity on the backend.
Movie Pundit Find your next flick by asking the (almost) all-knowing Movie Pundit Jump to Project Source » View Demo · Report Bug · Request Feature Ta
8 May 28, 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.
375 Dec 30, 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
70 Dec 05, 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
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QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
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.
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