chenchongthu's Stars
996icu/996.ICU
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
recommenders-team/recommenders
Best Practices on Recommendation Systems
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
thunlp/OpenKE
An Open-Source Package for Knowledge Embedding (KE)
Coder-Yu/QRec
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
xiangwang1223/knowledge_graph_attention_network
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
MaurizioFD/RecSys2019_DeepLearning_Evaluation
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
yangyutu/EssentialMath
drawbridge/keras-mmoe
A TensorFlow Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)
AmazingDD/daisyRec
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)
THUwangcy/ReChorus
“Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.
kuandeng/LightGCN
ShomyLiu/Neu-Review-Rec
A Toolkit for Neural Review-based Recommendation models with Pytorch.
piyushpathak03/Recommendation-systems
Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
xiangwang1223/disentangled_graph_collaborative_filtering
Disentagnled Graph Collaborative Filtering, SIGIR2020
chenchongthu/EHCF
This is our implementation of EHCF: Efficient Heterogeneous Collaborative Filtering (AAAI 2020)
Wenhui-Yu/LCFN
Codes for papers: 1. Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters (ICML). 2. Less is More: Exploring Simple and Powerful Low-pass Graph Convolutional Network for Recommendation. 3. Self-propagation Graph Neural Network for Recommendation (TKDE).
chenboability/CFM
chenchongthu/SAMN
This is our implementation of SAMN: Social Attentional Memory Network
THUwangcy/SLRC
WWW'2019: Modeling Item-Specific Temporal Dynamics of Repeat Consumption for Recommender Systems
chenchongthu/ENSFM
This is our implementation of ENSFM: Efficient Non-Sampling Factorization Machines (WWW 2020)
XinyuGuan01/Attentive-Aspect-based-Recommendation-Model
chenchongthu/EATNN
This is our implementation of EATNN: Efficient Adaptive Transfer Neural Network (SIGIR 2019)
chenchongthu/JNSKR
This is our implementation of JNSKR: Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation (SIGIR 2020)
ufozgg/DJClickModels
Click models by c++
Scagin/NeuralLogicReasoning
An Implementation of NLR: Neural Collaborative Reasoning, paper: https://arxiv.org/abs/2005.08129
Wenhui-Yu/NBPO
codes for SIGIR paper Sampler Design for Implicit Feedback Data by Noisy-label Robust Learning
THUIR/EHCF
THUxiexiaohui/An-image-dataset-with-preference-judgments
The image dataset in SIGIR 2020 paper "Preference-based Evaluation Metrics for Web Image Search"
cynthiayoung/LifeMusicData
LifeMusic dataset: Lifelog and music information when users listen to music