Identificacion Principal del registro INGC-EBK-000304

Control Number Identifier AR-LpUFI

LAST MODIFICATION DATE 20160829141500

CONTROL FIELD cr nn 008mamaa

CONTROL FIELD 131019s2014 gw | s |||| 0|eng d

a International Standard Book Number 9783319027111

a Standard number or code 10.1007/978-3-319-02711-1

a Personal name Gaber, Mohamed Medhat.

a Title Pocket Data Mining

h Medium [libro electrónico] : ;

b Remainder of title Big Data on Small Devices /

c Statement of responsibility, etc by Mohamed Medhat Gaber, Frederic Stahl, Joao Bártolo Gomes.

a Place of publication, distribution, etc Cham :

b Name of publisher, distributor, etc Springer International Publishing :

b Name of publisher, distributor, etc Imprint: Springer,

c Date of publication, distribution, etc 2014.

a Extent ix, 108 p. :

b Other physical details il.

a Series statement Studies in Big Data,

x International Standard Serial Number 2197-6503 ;

v Volume number/sequential designation 2

a Formatted contents note 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.

a 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.

a Topical term or geographic name as entry element Engineering.

a Topical term or geographic name as entry element Computational Intelligence.

a Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).

a Topical term or geographic name as entry element Data Mining and Knowledge Discovery.

a Personal name Stahl, Frederic.

a Personal name Gomes, Joao Bártolo,

u Uniform Resource Identifier (R) http://dx.doi.org/10.1007/978-3-319-02711-1

c item type EBK

a descripción COM