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Big Data Technologies and Applications

Overview of attention for book
Cover of 'Big Data Technologies and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Visualization of Mixed Attributed High-Dimensional Dataset Using Singular Value Decomposition
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    Chapter 2 Max-flow Min-cut Algorithm in Spark with Application to Road Networks
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    Chapter 3 Association Between Regional Difference in Heart Rate Variability and Inter-prefecture Ranking of Healthy Life Expectancy: ALLSTAR Big Data Project in Japan
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    Chapter 4 Allocation Four Neighbor Exclusive Channels to Polyhedron Clusters in Sensor Networks
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    Chapter 5 Feature Selection Techniques for Improving Rare Class Classification in Semiconductor Manufacturing Process
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    Chapter 6 A Novel Method for Extracting Dynamic Character Network from Movie
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    Chapter 7 Handling Uncertainty in Clustering Art-Exhibition Visiting Styles
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    Chapter 8 Using Geotagged Resources on Social Media for Cultural Tourism: A Case Study on Cultural Heritage Tourism
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    Chapter 9 Archaeological Site Image Content Retrieval and Automated Generating Image Descriptions with Neural Network
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    Chapter 10 Correcting Misspelled Words in Twitter Text
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    Chapter 11 Theoretical Concept of Inverse Kinematic Models to Determine Valid Work Areas Using Target Coordinates from NC-Programs
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    Chapter 12 Ransomware-Prevention Technique Using Key Backup
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    Chapter 13 Multi-level Steganography Based on Fuzzy Vault Systems and Secret Sharing Techniques
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    Chapter 14 On Exploiting Static and Dynamic Features in Malware Classification
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    Chapter 15 Distributed Compressive Sensing for Correlated Information Sources
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    Chapter 16 MMSE Based Interference Cancellation and Beamforming Scheme for Signal Transmission in IoT
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    Chapter 17 A Multi-user-collaboration Platform Concept for Managing Simulation-Based Optimization of Virtual Tooling as Big Data Exchange Service
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Big Data Technologies and Applications
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-58967-1
978-3-31-958967-1, 978-3-31-958966-4

Jason J. Jung, Kim Pankoo

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Engineering 1 50%
Unknown 1 50%