Pocket Data Mining (Record no. 57777)

000 -LEADER
fixed length control field 03352nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-319-02711-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112227.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131019s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319027111
-- 978-3-319-02711-1
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Gaber, Mohamed Medhat.
245 10 - TITLE STATEMENT
Title Pocket Data Mining
Sub Title Big Data on Small Devices /
300 ## - PHYSICAL DESCRIPTION
Number of Pages IX, 108 p. 46 illus.
490 1# - SERIES STATEMENT
Series statement Studies in Big Data,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Pocket Data Mining Framework -- Implementation of Pocket Data Mining -- Context-aware PDM(Coll-Stream) -- Experimental Validation of Context-aware PDM -- Potential Applications of Pocket Data Mining -- Conclusions, Discussion and Future Directions.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Stahl, Frederic.
700 1# - AUTHOR 2
Author 2 Gomes, Jo�ao B�artolo.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-02711-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2014.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2197-6503 ;
912 ## -
-- ZDB-2-ENG

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