DocumentCode :
2194988
Title :
Clutter-Adaptive Visualization for Mobile Data Mining
Author :
Gillick, Brett ; AlTaiar, Hasnain ; Krishnaswamy, Shonali ; Liono, Jonathan ; Nicoloudis, Nicholas ; Sinha, Abhijat ; Zaslavsky, Arkady ; Gaber, Mohamed Medhat
Author_Institution :
Centre for Distrib. Syst. & Software Eng., Monash Univ., Melbourne, VIC, Australia
fYear :
2010
fDate :
13-13 Dec. 2010
Firstpage :
1381
Lastpage :
1384
Abstract :
There is an emerging focus on real-time data stream analysis on mobile devices. While many mobile data stream mining algorithms have been developed in recent times, generic and scalable visualization techniques have not been presented. This paper presents the demonstration of our innovative clutter-adaptive cluster visualization technique for mobile devices. We have fully implemented this technique on the Google Android platform and provide demonstrations for different datasets: location (both real and synthetic), and stock-market (real).
Keywords :
data analysis; data mining; data visualisation; mobile computing; real-time systems; Google Android platform; clutter-adaptive visualization; generic visualization techniques; innovative clutter-adaptive cluster visualization technique; mobile data mining; mobile data stream mining algorithms; mobile devices; real-time data stream analysis; scalable visualization techniques; Mobile Data Mining; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-9244-2
Electronic_ISBN :
978-0-7695-4257-7
Type :
conf
DOI :
10.1109/ICDMW.2010.134
Filename :
5693458
Link To Document :
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