This library intends to be a reference for recommendation engines in Python

Overview
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
Owner
Marcel Caraciolo
Marcel Caraciolo
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

Jose A Dianes 794 Dec 23, 2022
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

ciecus 38 Dec 05, 2022
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

Milad Sadat-Mohammadi 1 Jan 21, 2022
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

Qitian Wu 78 Dec 10, 2022
A framework for large scale recommendation algorithms.

A framework for large scale recommendation algorithms.

Alibaba Group - PAI 880 Jan 03, 2023
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

Happy N. Monday 3 Feb 15, 2022
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

Cedric Niu 6 Nov 19, 2022
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

55 Dec 25, 2022
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

Wen Wang 18 Jan 02, 2023
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).

217 Jan 04, 2023
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

Aviem Zur 3 Apr 22, 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
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

Kapil Pramod Deshmukh 8 May 28, 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

98 Dec 28, 2022
6002project-rl - An implemention of offline RL on recommender system

An implemention of offline RL on recommender system @author: misajie @update: 20

Tzay Lee 3 May 24, 2022
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

International Business Machines 793 Dec 18, 2022
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

LI, Wai Yin 90 Oct 08, 2022
Respiratory Health Recommendation System

Respiratory-Health-Recommendation-System Respiratory Health Recommendation System based on Air Quality Index Forecasts This project aims to provide pr

Abhishek Gawabde 1 Jan 29, 2022
Plex-recommender - Get movie recommendations based on your current PleX library

plex-recommender Description: Get movie/tv recommendations based on your current

5 Jul 19, 2022
Recommender System Papers

Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021

RUCAIBox 704 Jan 06, 2023