开源推荐系统整理
花了大概1天的时间整理的各语言的开源推荐系统，比较完整全面的项目标红。
一、python库
1、benfred/implicit
Fast Python Collaborative Filtering for Implicit Datasets
https://github.com/benfred/implicit
2、Mendeley/mrec
A recommender systems development and evaluation package by Mendeley
https://github.com/mendeley/mrec
3、lyst/lightfm
A Python implementation of LightFM, a hybrid recommendation algorithm.
https://github.com/lyst/lightfm
4、MrChrisJohnson/logistic-mf
Logistic Matrix Factorization for Implicit Feedback Data.
https://github.com/MrChrisJohnson/logistic-mf
5、NicolasHug/Surprise
A Python scikit for building and analyzing recommender systems
https://github.com/NicolasHug/Surprise
6、ocelma/python-recsys
A python library for implementing a recommender system
https://github.com/ocelma/python-recsys
7、muricoca/crab
Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).
https://github.com/muricoca/crab
8、python-recsys/crab
Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (python, numpy, scipy, matplotlib)
https://github.com/python-recsys/crab
9、ibayer/fastFM
fastFM: A Library for Factorization Machines
https://github.com/ibayer/fastFM
10、jadianes/winerama-recommender-tutorial
A wine recommender system tutorial using Python technologies such as Django, Pandas, or Scikit-learn, and others such as Bootstrap.
https://github.com/jadianes/winerama-recommender-tutorial
二、java库
1、lenskit/lenskit
LensKit recommender toolkit
https://github.com/lenskit/lenskit
2、apache/mahout
The Apache Mahout™ project's goal is to build an environment for quickly creating scalable performant machine learning applications.
https://github.com/apache/mahout
3、myrrix/myrrix-recommender
Stand-alone recommender system from Myrrix
https://github.com/myrrix/myrrix-recommender
4、easyrec
Add recommendations to your website
http://easyrec.org/
5、SeldonIO/seldon-server
Enterprise machine learning platform for prediction and recommendation.
https://github.com/SeldonIO/seldon-server
6、rapidminer
RapidMiner makes data science teams more productive through a unified platform for data prep, machine learning, and model deployment.
https://rapidminer.com/
7、Duine Framework
a Java based recommendation system
https://sourceforge.net/projects/duine/
8、guoguibing/librec
LibRec: A Leading Java Library for Recommender Systems
https://github.com/guoguibing/librec/
9、RankSys/RankSys
Java 8 Recommender Systems framework for novelty, diversity and much more
https://github.com/RankSys/RankSys
10、learning-layers/TagRec
Towards A Standardized Tag Recommender Benchmarking Framework
https://github.com/learning-layers/TagRec
11、recommenders/rival
RiVal recommender system evaluation toolkit
https://github.com/recommenders/rival/
12、OryxProject/oryx
Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning
https://github.com/OryxProject/oryx
13、Waikato/moa
MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
https://github.com/Waikato/moa
三、C++库
1、Gnnng/SVDFeature
A recommend system I used before. The official website is http://svdfeature.apexlab.org/wiki/Ma
https://github.com/Gnnng/SVDFeature
2、cjlin1/libmf
LIBMF is a library for large-scale sparse matrix factorization. For the optimization problem it solves
https://github.com/cjlin1/libmf
3、srendle/libfm
Library for factorization machines
https://github.com/srendle/libfm
4、mikegashler/waffles
A toolkit of machine learning algorithms.
https://github.com/mikegashler/waffles
5、yixuan/recosystem
Recommender System Using Parallel Matrix Factorization
https://github.com/yixuan/recosystem
四、其他
1、apache/incubator-predictionio
PredictionIO, a machine learning server for developers and ML engineers. Built on Apache Spark, HBase and Spray.
https://github.com/apache/incubator-predictionio
2、guymorita/recommendationRaccoon
A collaborative filtering based recommendation engine and NPM module built on top of Node.js and Redis. The engine uses the Jaccard coefficient to determine the similarity between users and k-nearest-neighbors to create recommendations. This module is useful for anyone with a database of users, a database of products/movies/items and the desire …
https://github.com/guymorita/recommendationRaccoon
3、DataSystemsLab/recdb-postgresql
RecDB is a recommendation engine built entirely inside PostgreSQL
https://github.com/DataSystemsLab/recdb-postgresql
4、zenogantner/MyMediaLite
recommender system library for the CLR (.NET)
https://github.com/zenogantner/MyMediaLite
5、crowdrec/idomaar
Idomaar is the CrowdRec recommendation and evaluation reference framework.
https://github.com/crowdrec/idomaar/
6、grahamjenson/hapiger
HapiGer is an http-wrapper around the Good Enough Recommendation engine using the Hapi.js framework
https://github.com/grahamjenson/hapiger
7、OndraFiedler/spark-recommender
Scalable recommendation system written in Scala using the Apache Spark framework
https://github.com/OndraFiedler/spark-recommender