000 03352nam a22005175i 4500
001 978-3-319-02711-1
003 DE-He213
005 20200421112227.0
007 cr nn 008mamaa
008 131019s2014 gw | s |||| 0|eng d
020 _a9783319027111
_9978-3-319-02711-1
024 7 _a10.1007/978-3-319-02711-1
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aGaber, Mohamed Medhat.
_eauthor.
245 1 0 _aPocket Data Mining
_h[electronic resource] :
_bBig Data on Small Devices /
_cby Mohamed Medhat Gaber, Frederic Stahl, Jo�ao B�artolo Gomes.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aIX, 108 p. 46 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6503 ;
_v2
505 0 _aPocket 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 _aOwing 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.
650 0 _aEngineering.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aData Mining and Knowledge Discovery.
700 1 _aStahl, Frederic.
_eauthor.
700 1 _aGomes, Jo�ao B�artolo.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319027104
830 0 _aStudies in Big Data,
_x2197-6503 ;
_v2
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-02711-1
912 _aZDB-2-ENG
942 _cEBK
999 _c57777
_d57777