Information granularity, big data, and computational intelligence / Witold Pedrycz, Shyi-Ming Chen, editors.
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 transactions for a mega-retailer, weather?monitoring, intelligence gath...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
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Springer,
[2014]
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| Series: | Studies in big data ;
v. 8. |
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Table of Contents:
- Preface; Contents; Fundamentals; 1 Nearest Neighbor Queries on Big Data; Abstract; 1 ... Introduction; 2 ... Background; 3 ... System Model and Problem Formulation; 4 ... Related Work; 4.1 KNN Queries on Static Data; 4.2 Continuous KNN Queries; 4.3 All-KNN Queries in Distributed Systems; 4.4 Shortcomings of Existing Work; 5 ... The Proximity Framework; 5.1 Outline of Operation; 5.2 Constructing the Search Space; 5.3 Specialized Heap: The K+-Heap; 5.4 Insertion into the K+-Heap (Algorithm 2 and 3); 5.5 Running Example; 5.6 Performance Analysis; 6 ... Summary and Future Vision; References.
- 2 Information Mining for Big InformationAbstract; 1 ... Introduction; 2 ... Information Mining in Knowledge Discovery from Data; 3 ... Strong Relevant Logic-Based Reasoning as an Information Mining Method; 3.1 Deduction, Induction, and Abduction in Information Mining; 3.2 Formal Logic System and Formal Theory; 3.3 Reasoning with Strong Relevant Logics; 4 ... Supporting Tools for Information Mining with Strong Relevant Logic-Based Reasoning; 4.1 Forward Reasoning Engine; 4.2 Truth Maintenance System; 4.3 Epistemic Programming; 5 ... Summary; References.
- 3 Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression AnalysisAbstract; 1 ... Introduction; 2 ... Some Related Studies; 2.1 Recall of Real-Time Data Analysis Processing; 2.2 Brief Review on Granular Information; 2.3 Genetically-Guided Clustering Algorithm; 2.4 A Brief Review of a Convex Hull Approach; 2.4.1 Affine, Convex Hull Definition and Supporting Hyperplane; 2.4.2 Beneath-Beyond Algorithm; 2.5 A Convex Hull-Based Regression; 3 ... A Real-Time Granular Based Fuzzy Regression Models with a Convex Hull Implementation; 4 ... A Numerical Example and Performance Analysis.
- 5 ... Conclusion and Future WorksAcknowledgments; References; 4 How to Understand Connections Based on Big Data: From Cliques to Flexible Granules; Abstract; 1 ... Understanding Connections Based on Big Data: An Important Practical Problem; 2 ... General Case: How to Describe Available Information; 3 ... A Known Semi-heuristic Method for Detecting True Connections Based on Big Data: A Brief Description; 4 ... Limitations of the Semi-heuristic Approach; 5 ... Analysis of the Problem and the Resulting Ideas and Formulas; 6 ... Towards an Algorithm; 7 ... Resulting Algorithm; 8 ... Conclusions; Acknowledgements; References.
- 5 Graph-Based Framework for Evaluating the Feasibility of Transition to MaintainomicsAbstract; 1 ... Introduction; 2 ... Background; 2.1 What is Maintenance?; 2.2 What is e-Maintenance?; 2.3 What is Big Data?; 2.4 What is Maintainomics?; 3 ... Problem Statement; 4 ... Proposed Methodology; 4.1 Background of Graph Theory; 4.2 Background of Feasibility Index of Transition; 4.2.1 Visualizing Enablers' Correlation via Digraph; 4.2.2 Interpreting Enablers' Digraph Through Matrix; 4.2.3 Establishing the Matrix's Permanent Function Expression; 4.2.4 Creating FIT Value Scale; 4.2.5 Comparison; 4.2.6 Summary.