Pocket Data Mining
Big Data on Small Devices
Authors: Gaber, Mohamed Medhat, Stahl, Frederic, Gomes, Joao Bártolo
Free Preview- Introduction to "Pocket Data Mining"
- Describes the process of performing collaborative distributed data stream mining in the mobile computing environment
- Written by experts in the field
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- About this book
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Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
- Table of contents (8 chapters)
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Introduction
Pages 1-5
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Background
Pages 7-21
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Pocket Data Mining Framework
Pages 23-40
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Implementation of Pocket Data Mining
Pages 41-59
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Context-Aware PDM (Coll-Stream)
Pages 61-68
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Table of contents (8 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Pocket Data Mining
- Book Subtitle
- Big Data on Small Devices
- Authors
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- Mohamed Medhat Gaber
- Frederic Stahl
- Joao Bártolo Gomes
- Series Title
- Studies in Big Data
- Series Volume
- 2
- Copyright
- 2014
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-02711-1
- DOI
- 10.1007/978-3-319-02711-1
- Hardcover ISBN
- 978-3-319-02710-4
- Softcover ISBN
- 978-3-319-34686-1
- Series ISSN
- 2197-6503
- Edition Number
- 1
- Number of Pages
- IX, 108
- Number of Illustrations
- 46 b/w illustrations
- Topics
