Journal
KNOWLEDGE-BASED SYSTEMS
Volume 80, Issue -, Pages 98-108Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2014.12.030
Keywords
Data description; Granular computing; Information granules; Principle of justifiable granularity; Fuzzy clustering; Software data; Interpretation
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Funding
- Department for Educational Policies, Universities and Research of the Autonomous Province of Bolzano - South Tyrol
- Canada Research Chair (CRC)
- Natural Sciences and Engineering Research Council (NSERC)
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The study is concerned with a granular data description in which we propose a characterization of numeric data by a collection of information granules so that the key structure of the data, their topology and essential relationships are described in the form of a family of fuzzy sets - information granules. A comprehensive design process is introduced in which we show a two-phase development strategy: first, numeric prototypes are built with the use of Fuzzy C-Means (FCM) that is followed by their augmentation resulting in a collection of information granules. In the design of information granules we engage the fundamental ideas of Granular Computing, especially the principle of justifiable granularity. A series of experiments is presented to visualize the key steps of the construction of information granules. (C) 2015 Elsevier B.V. All rights reserved.
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