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Adaptive clutter-aware visualization for mobile data stream mining
School of Computing, University of Portsmouth.
Centre for Distributed Systems and Software Engineering, Monash University.
Centre for Distributed Systems and Software Engineering, Monash University.
Centre for Distributed Systems and Software Engineering, Monash University.
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2010 (English)In: 22nd International Conference on Tools with Artificial Intelligence: proceedings : 27-29 October 2010, Arras, France, Los Alamitos, Calif: IEEE Communications Society, 2010, 304-311 p.Conference paper (Refereed)
Abstract [en]

There is an emerging focus on real-time data stream analysis on mobile devices. A wide range of data stream processing applications are targeted to run on mobile handheld devices with limited computational capabilities such as patient monitoring, driver monitoring, providing real-time analysis and visualization for emergency and disaster management, real-time optimization for courier pick-up and delivery etc. There are many challenges in visualization of the analysis/data stream mining results on a mobile device. These include coping with the small screen real-estate and effective presentation of highly dynamic and real-time analysis. This paper proposes a generic theory for visualization on small screens that we term Adaptive Clutter Reduction ACR. Based on ACR, we have developed and experimentally validated a novel data stream clustering result visualization technique that we term Clutter-Aware Clustering Visualizer (CACV). Experimental results on both synthetic and real datasets using the Google Andriod platform are presented proving the effectiveness of the proposed techniques.

Place, publisher, year, edition, pages
Los Alamitos, Calif: IEEE Communications Society, 2010. 304-311 p.
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-38980DOI: 10.1109/ICTAI.2010.116Local ID: d8c0a8d3-8281-4688-9be2-0fb09a54a2faISBN: 9780769542638OAI: oai:DiVA.org:ltu-38980DiVA: diva2:1012488
Conference
International Conference on Tools with Artificial Intelligence : 27/10/2010 - 29/10/2010
Note
Godkänd; 2011; 20110131 (andbra)Available from: 2016-10-03 Created: 2016-10-03Bibliographically approved

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Zaslavsky, Arkady
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Computer Science

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