BMaD — A Boolean Matrix Decomposition Framework

Abstract

Boolean matrix decomposition is a method to obtain a compressed
representation of a matrix with Boolean entries. We present a modular
framework that unifies several Boolean matrix decomposition algorithms, and
provide methods to evaluate their performance. The main advantages of
the framework are its modular approach and hence the flexible
combination of the steps of a Boolean matrix decomposition and the
capability of handling missing values. The framework is licensed under
the GPLv3 and can be downloaded freely at
urlhttp://projects.informatik.uni-mainz.de/bmad.

Links

• http://dx.doi.org/10.1007/978-3-662-44845-8_40
• doi:10.1007/978-3-662-44845-8_40

BibTeX (Download)

@inproceedings{tyukin2014bmad,
title = {BMaD -- A Boolean Matrix Decomposition Framework},
author = {Andrey Tyukin and Stefan Kramer and Jörg Wicker},
editor = {Toon Calders and Floriana Esposito and Eyke Hüllermeier and Rosa Meo},
url = {http://dx.doi.org/10.1007/978-3-662-44845-8_40},
doi = {10.1007/978-3-662-44845-8_40},
isbn = {978-3-662-44844-1},
year  = {2014},
date = {2014-01-01},
booktitle = {Machine Learning and Knowledge Discovery in Databases},
volume = {8726},
pages = {481-484},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
abstract = {Boolean matrix decomposition is a method to obtain a compressed 
representation of a matrix with Boolean entries. We present a modular 
framework that unifies several Boolean matrix decomposition algorithms, and 
provide methods to evaluate their performance. The main advantages of 
the framework are its modular approach and hence the flexible 
combination of the steps of a Boolean matrix decomposition and the 
capability of handling missing values. The framework is licensed under 
the GPLv3 and can be downloaded freely at 
urlhttp://projects.informatik.uni-mainz.de/bmad.},
keywords = {Boolean matrix decomposition, framework},
pubstate = {published},
tppubtype = {inproceedings}
}