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Data Analytics and Management in Data Intensive Domains

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Cover of 'Data Analytics and Management in Data Intensive Domains'

Table of Contents

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    Book Overview
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    Chapter 1 Conceptualization of Methods and Experiments in Data Intensive Research Domains
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    Chapter 2 Semantic Search in a Personal Digital Library
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    Chapter 3 Digital Ecosystem OntoMath: Mathematical Knowledge Analytics and Management
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    Chapter 4 Development of Fuzzy Cognitive Map for Optimizing E-learning Course
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    Chapter 5 Supporting Biological Pathway Curation Through Text Mining
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    Chapter 6 Text Processing Framework for Emergency Event Detection in the Arctic Zone
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    Chapter 7 Fact Extraction from Natural Language Texts with Conceptual Modeling
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    Chapter 8 Hybrid Distributed Computing Service Based on the DIRAC Interware
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    Chapter 9 Hierarchical Multiple Stellar Systems
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    Chapter 10 Observations of Transient Phenomena in BSA Radio Survey at 110 MHz
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    Chapter 11 Semantics and Verification of Entity Resolution and Data Fusion Operations via Transformation into a Formal Notation
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    Chapter 12 A Study of Several Matrix-Clustering Vertical Partitioning Algorithms in a Disk-Based Environment
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    Chapter 13 Clustering of Goods and User Profiles for Personalizing in E-commerce Recommender Systems Based on Real Implicit Data
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    Chapter 14 On Data Persistence Models for Mobile Crowdsensing Applications
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    Chapter 15 The European Strategy in Research Infrastructures and Open Science Cloud
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    Chapter 16 Creating Inorganic Chemistry Data Infrastructure for Materials Science Specialists
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    Chapter 17 Visual Analytics of Multidimensional Dynamic Data with a Financial Case Study
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    Chapter 18 Metadata for Experiments in Nanoscience Foundries
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    Chapter 19 Metrics and Rankings: Myths and Fallacies
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Citations

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Title
Data Analytics and Management in Data Intensive Domains
Published by
Springer, Cham, January 2016
DOI 10.1007/978-3-319-57135-5
ISBNs
978-3-31-957134-8, 978-3-31-957135-5
Editors

Leonid Kalinichenko, Sergei O. Kuznetsov, Yannis Manolopoulos

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

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 > Bachelor 4 200%
Student > Postgraduate 4 200%
Unspecified 3 150%
Student > Master 2 100%
Professor 2 100%
Other 6 300%
Readers by discipline Count As %
Computer Science 9 450%
Unspecified 3 150%
Engineering 3 150%
Agricultural and Biological Sciences 2 100%
Biochemistry, Genetics and Molecular Biology 1 50%
Other 3 150%

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