Towards an Optimal Task-Driven Information Granulation

Chapter

Abstract

In this work we have analyzed Big Data sources and made a conclusion that sizeable part of them is people-generated data. We can present this type of data in form of qualitative attributes. The model of such attributes is a collection of fuzzy granules. We also need to granulate the data for application of a big part of analytical technologies. When we form the granules, we have a choice among different variants. Which of them is good for specific task? How can we measure this “goodness” and make a choice the best (optimal) granulation? We provide our vision of answers on these questions in the chapter.

Keywords

Big data Fuzzy information granulation Fuzzy linguistic scales Measure of fuzziness Loss of information and information noise for fuzzy data 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Mathematical Foundations of Intelligent Systems, Department of Mechanics and MathematicsLomonosov’ Moscow State UniversityMoscowRussia

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