142 Repositories
Python odp-recommendation Libraries
A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.
Torch-RecHub A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend. 安装 pip install torch-rechub 主要特性 scikit-learn风格易用
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
Smooth ReLU in PyTorch Unofficial PyTorch reimplementation of the Smooth ReLU (SmeLU) activation function proposed in the paper Real World Large Scale
一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM,xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... (pytorch, tf2.0)
CTR Algorithm 根据论文, 博客, 知乎等方式学习一些CTR相关的算法 理解原理并自己动手来实现一遍 pytorch & tf2.0 保持一颗学徒的心! Schedule Model pytorch tensorflow2.0 paper LR ✔️ ✔️ \ FM ✔️ ✔️ Fac
Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation'
OD-Rec Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation' Paper, saved teacher models and Andro
Official repository for "Exploiting Session Information in BERT-based Session-aware Sequential Recommendation", SIGIR 2022 short.
Session-aware BERT4Rec Official repository for "Exploiting Session Information in BERT-based Session-aware Sequential Recommendation", SIGIR 2022 shor
[SIGIR22] Official PyTorch implementation for "CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space".
CORE This is the official PyTorch implementation for the paper: Yupeng Hou, Binbin Hu, Zhiqiang Zhang, Wayne Xin Zhao. CORE: Simple and Effective Sess
Session-based Recommendation, CoHHN, price preferences, interest preferences, Heterogeneous Hypergraph, Co-guided Learning, SIGIR2022
This is our implementation for the paper: Price DOES Matter! Modeling Price and Interest Preferences in Session-based Recommendation Xiaokun Zhang, Bo
Official public repository of paper "Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation"
Intention Adaptive Graph Neural Network (IAGNN) This is the official repository of paper Intention Adaptive Graph Neural Network for Category-Aware Se
Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity
Product-based-recommendation-system A product based recommendation system which
OntoSeer is a tool to help users build better quality ontologies
Ontoseer This document provides documentation for the first version of OntoSeer.OntoSeer is a tool that monitors the ontology development process andp
Recommender systems are the systems that are designed to recommend things to the user based on many different factors
Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.
A notebook to analyze Amazon Recommendation Review Dataset.
Amazon Recommendation Review Dataset Analyzer A notebook to analyze Amazon Recommendation Review Dataset. Features Calculates distinct user count, dis
Cloud-based recommendation system
This project is based on cloud services to create data lake, ETL process, train and deploy learning model to implement a recommendation system.
Bert4rec for news Recommendation
News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation
[제 13회 투빅스 컨퍼런스] OK Mugle! - 장르부터 멜로디까지, Content-based Music Recommendation
Ok Mugle! 🎵 장르부터 멜로디까지, Content-based Music Recommendation 'Ok Mugle!'은 제13회 투빅스 컨퍼런스(2022.01.15)에서 진행한 음악 추천 프로젝트입니다. Description 📖 본 프로젝트에서는 Kakao
Respiratory Health Recommendation System
Respiratory-Health-Recommendation-System Respiratory Health Recommendation System based on Air Quality Index Forecasts This project aims to provide pr
Laporan Proyek Machine Learning - Azhar Rizki Zulma
Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu
Recommendation Systems for IBM Watson Studio platform
Recommendation-Systems-for-IBM-Watson-Studio-platform Project Overview In this project, I analyze the interactions that users have with articles on th
This library intends to be a reference for recommendation engines in Python
Crab - A Python Library for Recommendation Engines
The PyTorch implementation of paper REST: Debiased Social Recommendation via Reconstructing Exposure Strategies
REST The PyTorch implementation of paper REST: Debiased Social Recommendation via Reconstructing Exposure Strategies. Usage Download dataset Download
Sentiment Based Product Recommendation System
Sentiment Based Product Recommendation System The e-commerce business is quite p
Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation
SUCP Leveraging Social Influence based on Users Activity Centers for Point-of-Interest Recommendation () Direct Friends (i.e., users who follow each o
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can
This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation).
FlatGCN This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation, submitted to ICASSP2022). Req
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
A recommendation system for suggesting new books given similar books.
Book Recommendation System A recommendation system for suggesting new books given similar books. Datasets Dataset Kaggle Dataset Notebooks goodreads-E
Recommendationsystem - Movie-recommendation - matrixfactorization colloborative filtering recommendation system user
recommendationsystem matrixfactorization colloborative filtering recommendation
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Introduction 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
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Movie recommendation using RASA, TigerGraph
Demo run: The below video will highlight the runtime of this setup and some sample real-time conversations using the power of RASA + TigerGraph, Steps
Books Recommendation With Python
Books-Recommendation Business Problem During the last few decades, with the rise
DeepRec is a recommendation engine based on TensorFlow.
DeepRec Introduction DeepRec is a recommendation engine based on TensorFlow 1.15, Intel-TensorFlow and NVIDIA-TensorFlow. Background Sparse model is a
Deploy recommendation engines with Edge Computing
RecoEdge: Bringing Recommendations to the Edge A one stop solution to build your recommendation models, train them and, deploy them in a privacy prese
Source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network
D-HAN The source code of D-HAN This is the source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network. However, only the co
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
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
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Introduction 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
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
This is the official source code of "BiCAT: Bi-Chronological Augmentation of Transformer for Sequential Recommendation".
BiCAT This is our TensorFlow implementation for the paper: "BiCAT: Sequential Recommendation with Bidirectional Chronological Augmentation of Transfor
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion
Machine Learning for Argument-Based Computational Persuasion This repo contains the source code and a benchmark for predicting user's utilities with M
Download and preprocess popular sequential recommendation datasets
Sequential Recommendation Datasets This repository collects some commonly used sequential recommendation datasets in recent research papers and provid
Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation
Tiny-NewsRec The source codes for our paper "Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation". Requirements PyTorch == 1.6.0 Tensor
Adaptive Denoising Training (ADT) for Recommendation.
DenoisingRec Adaptive Denoising Training for Recommendation. This is the pytorch implementation of our paper at WSDM 2021: Denoising Implicit Feedback
Pytorch domain library for recommendation systems
TorchRec (Experimental Release) TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale
FPE - Format Preserving Encryption with FF3 in Python
ff3 - Format Preserving Encryption in Python An implementation of the NIST approved FF3 and FF3-1 Format Preserving Encryption (FPE) algorithms in Pyt
Randomly picks between your favourite meals for you when you're feeling indecisive.
Food Recommendations Desktop application created with python and tkinter. The goal for this application is to provide a way for users to enter and sav
Robust & Reliable Route Recommendation on Road Networks
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks This repository is the official implementation of NeuroMLR: Robust & Reliable Route
This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation withNoisy Multi-feedback"
Curriculum_disentangled_recommendation This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation with Noisy Multi-feedb
The implementation of our CIKM 2021 paper titled as: "Cross-Market Product Recommendation"
FOREC: A Cross-Market Recommendation System This repository provides the implementation of our CIKM 2021 paper titled as "Cross-Market Product Recomme
E-Commerce recommender demo with real-time data and a graph database
🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str
High performance distributed framework for training deep learning recommendation models based on PyTorch.
PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It
A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.
TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction 论文:Time Interval Aware Sel
Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".
SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph
A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize
⚡ funk-svd funk-svd is a Python 3 library implementing a fast version of the famous SVD algorithm popularized by Simon Funk during the Neflix Prize co
The source code and dataset for the RecGURU paper (WSDM 2022)
RecGURU About The Project Source code and baselines for the RecGURU paper "RecGURU: Adversarial Learning of Generalized User Representations for Cross
GNN-based Recommendation Benchmark
GRecX A Fair Benchmark for GNN-based Recommendation Homepage and Documentation Homepage: Documentation: Paper: GRecX: An Efficient and Unified Benchma
A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework
music-recommender-rest-api A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework How it works T
A Recommendation System For Diabetes Detection And Treatment
Diabetes-detection-tg-bot A Recommendation System For Diabetes Detection And Treatment Данная система помогает определить наличие или отсутствие сахар
PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021.
PAML PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021. (Continuously updating ) Int
High performance distributed framework for training deep learning recommendation models based on PyTorch.
High performance distributed framework for training deep learning recommendation models based on PyTorch.
Session-aware Item-combination Recommendation with Transformer Network
Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations
TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations Requirements python 3.6 torch 1.9 numpy 1.19 Quick Start The experimen
Recommendation System to recommend top books from the dataset
recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als
Fair Recommendation in Two-Sided Platforms
Fair Recommendation in Two-Sided Platforms
Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks
Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks This is our Pytorch implementation for the paper: Zirui Zhu, Chen Gao, Xu C
Pytorch implementation for the paper: Contrastive Learning for Cold-start Recommendation
Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L
Deep Learning Based Fasion Recommendation System for Ecommerce
Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod
Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback
Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback This is our Pytorch implementation for the paper: Yinwei Wei,
UV matrix decompostion using movielens dataset
UV-matrix-decompostion-with-kfold UV matrix decompostion using movielens dataset upload the 'ratings.dat' file install the following python libraries
PyTorch implementation for "Mining Latent Structures with Contrastive Modality Fusion for Multimedia Recommendation"
MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.
Locally Constrained Self-Attentive Sequential Recommendation
LOCKER This is the pytorch implementation of this paper: Locally Constrained Self-Attentive Sequential Recommendation. Zhankui He, Handong Zhao, Zhe L
UltraGCN: An Ultra Simplification of Graph Convolutional Networks for Recommendation
UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A
Spotify Song Recommendation Program
Spotify-Song-Recommendation-Program Made by Esra Nur Özüm Written in Python The aim of this project was to build a recommendation system that recommen
GNN-based Recommendation Benchma
GRecX A Fair Benchmark for GNN-based Recommendation Preliminary Comparison DiffNet-Yelp dataset (featureless) Algo nDCG@5 nDCG@10 nDCG@15 MF 0.158707
Hierarchical User Intent Graph Network for Multimedia Recommendation
Hierarchical User Intent Graph Network for Multimedia Recommendation This is our Pytorch implementation for the paper: Hierarchical User Intent Graph
Out-of-Town Recommendation with Travel Intention Modeling (AAAI2021)
TrainOR_AAAI21 This is the official implementation of our AAAI'21 paper: Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou, Hui Xiong
This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.
Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR) This is the official implementation of our paper Personalized Tran
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR)
This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.
Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.
Graph Mining Author: Jiayi Chen Time: April 2021 Implemented Algorithms: Network: Scrabing Data, Network Construbtion and Network Measurement (e.g., P
Recommendation algorithms for large graphs
Fast recommendation algorithms for large graphs based on link analysis. License: Apache Software License Author: Emmanouil (Manios) Krasanakis Depende
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
Temporal Meta-path Guided Explainable Recommendation (WSDM2021)
Temporal Meta-path Guided Explainable Recommendation (WSDM2021) TMER Code of paper "Temporal Meta-path Guided Explainable Recommendation". Requirement
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
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
The official implementation of "DGCN: Diversified Recommendation with Graph Convolutional Networks" (WWW '21)
DGCN This is the official implementation of our WWW'21 paper: Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li, DGCN: Diversified Recommendation wi
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
Code for my ORSUM, ACM RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation
HeroGRAPH Code for my ORSUM @ RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation Paper, workshop pro
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks
Bi-TGCF Tensorflow Implementation of BiTGCF: Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20
Cross-Domain Recommendation via Preference Propagation GraphNet.
PPGN Codes for CIKM 2019 paper Cross-Domain Recommendation via Preference Propagation GraphNet. Citation Please cite our paper if you find this code u
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
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
An Efficient and Effective Framework for Session-based Social Recommendation
SEFrame This repository contains the code for the paper "An Efficient and Effective Framework for Session-based Social Recommendation". Requirements P
Codes for AAAI'21 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'
DHCN Codes for AAAI 2021 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'. Please note that the default link
[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
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation
MKM-SR Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation Paper data and code This is the
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
Handling Information Loss of Graph Neural Networks for Session-based Recommendation
LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro
This is our Tensorflow implementation for "Graph-based Embedding Smoothing for Sequential Recommendation" (GES) (TKDE, 2021).
Graph-based Embedding Smoothing (GES) This is our Tensorflow implementation for the paper: Tianyu Zhu, Leilei Sun, and Guoqing Chen. "Graph-based Embe