ScalableNMF: Scalable Nonnegative Matrix Factorization

1. Introduction

ScalableNMF is the implementation of Scalable Nonnegative Matrix Factorization introduced in the paper Scalable Nonnegative Matrix Factorization with Block-wise Updates
(Jiangtao Yin, Lixin Gao, and Zhongfei Zhang) in ECML/PKDD 2014.

ScalableNMF supports Nonnegative Matrix Factorization at a million-by-million scale. It is implemented in Java for the Hadoop platform and is free to distribute for non-commercial usage. 

2. Preparation

A Hadoop cluster should be running, configured in either pseudo-distributed or cluster mode. To deploy a Hadoop cluster environment, you can refer to Hadoop cluster setup instructions
if you've never used Hadoop (we recommend Hadoop 0.20.2 or above for compatibility).

3. Usage

Download the package, ScalableNMF.tar.gz

See the README file inside the package for usage instructions.

Please contact Jiangtao if you run into any issues (
jyin AT ecs DOT umass DOT edu).