Resumen

LAPEIRA MENA, Orenia; CERUTO CORDOVES, Taymi; ROSETE SUAREZ, Alejandro  y  DIAZ PANDO, Humberto. Algoritmo paralelo para la obtención de predicados difusos: Parallel Algorithm to obtain fuzzy predicates. Rev cuba cienc informat [online]. 2017, vol.11, n.2, pp. 117-133. ISSN 2227-1899.

ABSTRACT The rapid development in several fields of science and engineering, requires the design of novel computational techniques that allow processing large amounts of data, reducing response times and enabling the treatment of complex problems. FuzzyPred is a data mining method that allows obtaining fuzzy predicates in normal forms. For this method the size of the database is an essential factor in the response time of the algorithm, as each predicate is evaluated in each of the records in the database. When process is performed sequentially, it does not employ current hardware architectures that exist today for processing large volumes of data. This results in long runtimes, depending of the size of the database. This paper proposes a parallelized version of FuzzyPred, based on the amount of data that can be processed within each processing threads, synchronously and independent. The results obtained during experimentation indicate that the parallel algorithm is up to 10 times faster than the sequential version and that is why it is considered that can be very useful in improving the efficiency of the algorithm in very large databases.

Palabras clave : Data parallelization; Fuzzy Predicates; Data Mining..

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