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Data Science and Big Data Computing

Overview of attention for book
Data Science and Big Data Computing
Springer International Publishing

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 11: A Framework for Data Mining and Knowledge Discovery in Cloud Computing
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