Pocket Data Mining: Big Data on Small Devices
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schriftenreihe: | Studies in Big Data
2 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (IX, 108 p.) 46 illus |
| ISBN: | 9783319027111 |
Internformat
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| 490 | 1 | |a Studies in Big Data |v 2 | |
| 500 | |a 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 | ||
| 505 | 0 | |a 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 | |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | 1015918 |
|---|---|
| _version_ | 1806174845257383936 |
| adam_text | POCKET DATA MINING
/ GABER, MOHAMED MEDHAT
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
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
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
POCKET DATA MINING
/ GABER, MOHAMED MEDHAT
: 2014
ABSTRACT / INHALTSTEXT
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
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Gaber, Mohamed Medhat |
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| contents | 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 |
| ctrlnum | (OCoLC)865039929 (DE-599)BVBBV041471000 |
| dewey-full | 006.3 |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-08-01T10:56:00Z |
| institution | BVB |
| isbn | 9783319027111 |
| language | English |
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| physical | 1 Online-Ressource (IX, 108 p.) 46 illus |
| psigel | ZDB-2-ENG |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| record_format | marc |
| series | Studies in Big Data |
| series2 | Studies in Big Data |
| spellingShingle | Gaber, Mohamed Medhat Pocket Data Mining Big Data on Small Devices Studies in Big Data 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 Engineering Data mining Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz |
| title | Pocket Data Mining Big Data on Small Devices |
| title_auth | Pocket Data Mining Big Data on Small Devices |
| title_exact_search | Pocket Data Mining Big Data on Small Devices |
| title_full | Pocket Data Mining Big Data on Small Devices by Mohamed Medhat Gaber, Frederic Stahl, João Bártolo Gomes |
| title_fullStr | Pocket Data Mining Big Data on Small Devices by Mohamed Medhat Gaber, Frederic Stahl, João Bártolo Gomes |
| title_full_unstemmed | Pocket Data Mining Big Data on Small Devices by Mohamed Medhat Gaber, Frederic Stahl, João Bártolo Gomes |
| title_short | Pocket Data Mining |
| title_sort | pocket data mining big data on small devices |
| title_sub | Big Data on Small Devices |
| topic | Engineering Data mining Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz |
| topic_facet | Engineering Data mining Artificial intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Ingenieurwissenschaften Künstliche Intelligenz |
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