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Data Science and Big Data Computing

Overview of attention for book
Cover of 'Data Science and Big Data Computing'

Table of Contents

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    Book Overview
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    Chapter 1 An Interoperability Framework and Distributed Platform for Fast Data Applications
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    Chapter 2 Complex Event Processing Framework for Big Data Applications
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    Chapter 3 Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
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    Chapter 4 Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective
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    Chapter 5 A Unified Approach to Data Modeling and Management in Big Data Era
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    Chapter 6 Interfacing Physical and Cyber Worlds: A Big Data Perspective
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    Chapter 7 Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data
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    Chapter 8 An Analytics-Driven Approach to Identify Duplicate Bug Records in Large Data Repositories
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    Chapter 9 Large-Scale Data Analytics Tools: Apache Hive, Pig, and HBase
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    Chapter 10 Big Data Analytics: Enabling Technologies and Tools
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    Chapter 11 A Framework for Data Mining and Knowledge Discovery in Cloud Computing
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    Chapter 12 Feature Selection for Adaptive Decision Making in Big Data Analytics
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    Chapter 13 Social Impact and Social Media Analysis Relating to Big Data
Attention for Chapter 3: Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
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Chapter title
Agglomerative Approaches for Partitioning of Networks in Big Data Scenarios
Chapter number 3
Book title
Data Science and Big Data Computing
Published by
Springer International Publishing, July 2016
DOI 10.1007/978-3-319-31861-5_3
Book ISBNs
978-3-31-931859-2, 978-3-31-931861-5
Authors

Anupam Biswas, Gourav Arora, Gaurav Tiwari, Srijan Khare, Vyankatesh Agrawal, Bhaskar Biswas

Editors

Zaigham Mahmood

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X Demographics

The data shown below were collected from the profiles of 2 X users 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Researcher 1 33%
Student > Doctoral Student 1 33%
Readers by discipline Count As %
Computer Science 3 100%

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