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Data Science and Big Data: An Environment of Computational Intelligence

Overview of attention for book
Cover of 'Data Science and Big Data: An Environment of Computational Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Large-Scale Clustering Algorithms
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    Chapter 2 On High Dimensional Searching Spaces and Learning Methods
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    Chapter 3 Enhanced Over_Sampling Techniques for Imbalanced Big Data Set Classification
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    Chapter 4 Online Anomaly Detection in Big Data: The First Line of Defense Against Intruders
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    Chapter 5 Developing Modified Classifier for Big Data Paradigm: An Approach Through Bio-Inspired Soft Computing
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    Chapter 6 Unified Framework for Control of Machine Learning Tasks Towards Effective and Efficient Processing of Big Data
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    Chapter 7 An Efficient Approach for Mining High Utility Itemsets Over Data Streams
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    Chapter 8 Event Detection in Location-Based Social Networks
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    Chapter 9 Using Computational Intelligence for the Safety Assessment of Oil and Gas Pipelines: A Survey
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    Chapter 10 Big Data for Effective Management of Smart Grids
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    Chapter 11 Distributed Machine Learning on Smart-Gateway Network Towards Real-Time Indoor Data Analytics
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    Chapter 12 Predicting Spatiotemporal Impacts of Weather on Power Systems Using Big Data Science
Attention for Chapter 7: An Efficient Approach for Mining High Utility Itemsets Over Data Streams
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Citations

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Chapter title
An Efficient Approach for Mining High Utility Itemsets Over Data Streams
Chapter number 7
Book title
Data Science and Big Data: An Environment of Computational Intelligence
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-53474-9_7
Book ISBNs
978-3-31-953473-2, 978-3-31-953474-9
Authors

Show-Jane Yen, Yue-Shi Lee

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 100%
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Computer Science 1 100%
Engineering 1 100%

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