Crab - A Python Library for Recommendation Engines This library intends to be a reference for recommendation engines in Python Programming language. It is written in pure python to maximize the cross-platform issue and exposes the recommendation logic to your application by easy to use API REST via web services. The library is extensible, so the user can create new representations, algorithms and the design is optimized for performance. It is also open-source so everyone can use it. If you want to see our plan release/roadmap, please take a look at our Issues Tracker: http://github.com/marcelcaraciolo/crab/issues
This library intends to be a reference for recommendation engines in Python
Overview
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
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation
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Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
DANSER-WWW-19 This repository holds the codes for Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recom
A framework for large scale recommendation algorithms.
A framework for large scale recommendation algorithms.
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 filte
基于个性化推荐的音乐播放系统
MusicPlayer 基于个性化推荐的音乐播放系统 Hi, 这是我在大四的时候做的毕设,现如今将该项目开源。 本项目是基于Python的tkinter和pygame所著。 该项目总体来说,代码比较烂(因为当时水平很菜)。 运行的话安装几个基本库就能跑,只不过里面的数据还没有上传至Github。 先
Bundle Graph Convolutional Network
Bundle Graph Convolutional Network This is our Pytorch implementation for the paper: Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin and Yong Li. Bun
Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction
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
Graph Neural Networks for Recommender Systems
This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).
Movies/TV Recommender
recommender Movies/TV Recommender. Recommends Movies, TV Shows, Actors, Directors, Writers. Setup Create file API_KEY and paste your TMDB API key in i
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
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
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
6002project-rl - An implemention of offline RL on recommender system
An implemention of offline RL on recommender system @author: misajie @update: 20
Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch
Recommendation engines are one of the most well known, widely used and highest value use cases for applying machine learning. Despite this, while there are many resources available for the basics of
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms
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
Respiratory Health Recommendation System
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Plex-recommender - Get movie recommendations based on your current PleX library
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Recommender System Papers
Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021