Titlebook: Information Granularity, Big Data, and Computational Intelligence; Witold Pedrycz,Shyi-Ming Chen Book 2015 Springer International Publishi

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Nearest Neighbor Queries on Big Databased on a novel data structure, coined ..-heap. ., being parameter-free, performs efficiently in the face of high velocity and skewed data. In our analytical studies, we found that . provides better time complexity compared to existing approaches and is very well suited for large scale scenarios.

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Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis the computing time, especially in case of real-time data analysis, as well as an overall computational complexity. Additionally, the proposed approach shows an efficient real-time processing of information granules regression analysis based on the convex hull approach in which a Beneath-Beyond algo

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How to Understand Connections Based on Big Data: From Cliques to Flexible Granulessonably successful. The second limitation is that this heuristic method is based on using “crisp” granules (clusters), while in reality, the corresponding granules are flexible (“fuzzy”). In this chapter, we explain how the known semi-heuristic method can be justified in statistical terms, and we al

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The Property of Different Granule and Granular Methods Based on Quotient Spacenly it can represent vectors of the problem domain, different structures between vectors, but also it can define different attribute functions and operations etc. In this paper, we discuss the method how to represent and to partition an object in granular worlds, and educe the relationship of differ

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2197-6503 duction to Computational Intelligence.Self-contained and eas.The recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry and government organizations. Data sets such as customer transactio