Parallel exploration of partial solutions in Boolean matrix factorization

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F19%3A73595308" target="_blank" >RIV/61989592:15310/19:73595308 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0743731518306968" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0743731518306968</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jpdc.2018.09.014" target="_blank" >10.1016/j.jpdc.2018.09.014</a>

Result language
angličtina
Original language name
Parallel exploration of partial solutions in Boolean matrix factorization
Original language description
Boolean matrix factorization (BMF) is a well established method for preprocessing and analysis of data. There is a number of algorithms for BMF, but none of them uses benefits of parallelization. This is mainly due to the fact that many of the algorithms utilize greedy heuristics that are inherently sequential. In this work, we propose a general parallelization scheme for BMF in which several locally optimal partial matrix decompositions are constructed simultaneously in parallel, instead of just one in a sequential algorithm. As a result of the computation, either the single best final decomposition or several top-k of them may be returned. The scheme can be applied to any sequential heuristic BMF algorithm and we show the application on two representative algorithms, namely GRECOND and ASSO. Improvements in decompositions are presented via results from experiments with the new algorithms on synthetic and real datasets
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GA15-17899S" target="_blank" >GA15-17899S: Decompositions of Matrices with Boolean and Ordinal Data: Theory and Algorithms</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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