Granular rough computing selected methods for data size reduction

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Piotr Artiemjew and Lech Polkowski

University of Warmia and Mazury, Poland
Polish-Japanese Academy of Information Technology, Poland

: J Comput Eng Inf Technol

Abstract

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The goal of this talk is to present the selected recent methods from the area of granular computing with their potential application to the big data. Introduced by Prof. Lotfi A Zadeh, granular computing consists of compressing knowledge from individual objects into granules i.e. clumps of objects drawn together by some form of similarity. Computing with granules reduces noise in data and speeds up computations. The talk is based on the book by Polkowski and Artiemjew: “Granular Computing in Decision Approximation”. In the recent years, the rapid development in this field can be observed. There are many methods, which are potentially useful in size reduction of data with maintenance of the internal knowledge. The granular computing is one of the future fields of data exploration research. Its uniqueness is determined by the human centered profile of methods giving us more natural thinking about the data exploration.

Biography

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Email: piotr.artiemjew@uwm.edu.pl