Parallel Execution of Binary-Based NextClosure Algorithm
Date issued
July 18, 2016
Subjects
Formal concept analysis NextClosure Parallel programming Binary computation
Abstract
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
Event name
The International Workshop on Algorithms for FCA and Data Mining (AFCADM 2016)
Location
Moscow, Russia
Publication type
conference paper
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