Minimal generators, an affordable approach by means of massive computation

Minimal generators, an affordable approach by means of massive computation J Supercomput https://doi.org/10.1007/s11227-018-2453-z Minimal generators, an affordable approach by means of massive computation 1 1 1 F. Benito-Picazo · P. Cordero · M. Enciso · A. Mora © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Closed sets and minimal generators are fundamental elements to build a complete knowledge representation in formal concept analysis. The enumeration of all the closed sets and their minimal generators from a set of rules or implications constitutes a complex problem, drawing an exponential cost. Even for small datasets, such representation can demand an exhaustive management of the information stored as attribute implications. In this work, we tackle this problem by merging two strate- gies. On the one hand, we design a pruning, strongly based on logic properties, to drastically reduce the search space of the method. On the other hand, we consider a parallelization of the problem leading to a massive computation by means of a map- reduce like paradigm. In this study we have characterized the type of search space reductions suitable for parallelization. Also, we have analyzed different situations to provide an orientation of the resources (number of cores) needed for both the parallel architecture and the size of http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Supercomputing Springer Journals

Minimal generators, an affordable approach by means of massive computation

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Programming Languages, Compilers, Interpreters; Processor Architectures; Computer Science, general
ISSN
0920-8542
eISSN
1573-0484
D.O.I.
10.1007/s11227-018-2453-z
Publisher site
See Article on Publisher Site

Abstract

J Supercomput https://doi.org/10.1007/s11227-018-2453-z Minimal generators, an affordable approach by means of massive computation 1 1 1 F. Benito-Picazo · P. Cordero · M. Enciso · A. Mora © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Closed sets and minimal generators are fundamental elements to build a complete knowledge representation in formal concept analysis. The enumeration of all the closed sets and their minimal generators from a set of rules or implications constitutes a complex problem, drawing an exponential cost. Even for small datasets, such representation can demand an exhaustive management of the information stored as attribute implications. In this work, we tackle this problem by merging two strate- gies. On the one hand, we design a pruning, strongly based on logic properties, to drastically reduce the search space of the method. On the other hand, we consider a parallelization of the problem leading to a massive computation by means of a map- reduce like paradigm. In this study we have characterized the type of search space reductions suitable for parallelization. Also, we have analyzed different situations to provide an orientation of the resources (number of cores) needed for both the parallel architecture and the size of

Journal

The Journal of SupercomputingSpringer Journals

Published: Jun 4, 2018

References

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