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Parallel Execution of Binary-Based NextClosure Algorithm
Date de parution
2016-7-18
Résumé
Formal concept analysis (FCA) has become a popular method
for analyzing data across various domains in which data bases can be
analyzed regardless of their contexts. With its properties FCA is of big
interest in the context of Big Data. However, the complexity of the basic
FCA analysis algorithms often prohibits its use in general production
tool chains for data analysis. In this paper we show how to overcome
some of these problems. In the first step we show how to implement the
well known NextClosure in efficient way in Python (a preferred language
in the context of ad-hoc data analysis) which is several times faster the
other published algorithms. In the second step we show how our implementation
can be parallelized on common hardware by strictly using the
best sequential algorithm which di↵ers in an important way form so far
published parallel algorithms for FCA.
for analyzing data across various domains in which data bases can be
analyzed regardless of their contexts. With its properties FCA is of big
interest in the context of Big Data. However, the complexity of the basic
FCA analysis algorithms often prohibits its use in general production
tool chains for data analysis. In this paper we show how to overcome
some of these problems. In the first step we show how to implement the
well known NextClosure in efficient way in Python (a preferred language
in the context of ad-hoc data analysis) which is several times faster the
other published algorithms. In the second step we show how our implementation
can be parallelized on common hardware by strictly using the
best sequential algorithm which di↵ers in an important way form so far
published parallel algorithms for FCA.
Notes
, 2016
Nom de l'événement
The International Workshop on Algorithms for FCA and Data Mining (AFCADM 2016)
Lieu
Moscow, Russia
Identifiants
Type de publication
conference paper
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