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Situation-Aware Adaptive Visualization for Sensory Data Stream Mining

  • Pari Delir Haghighi
  • Brett Gillick
  • Shonali Krishnaswamy
  • Mohamed Medhat Gaber
  • Arkady Zaslavsky
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5840)

Abstract

With the emergence of ubiquitous data mining and recent advances in mobile communications, there is a need for visualization techniques to enhance the user-interactions, real-time decision making and comprehension of the results of mining algorithms. In this paper we propose a novel architecture for situation-aware adaptive visualization that applies intelligent visualization techniques to data stream mining of sensory data. The proposed architecture incorporates fuzzy logic principles for modeling and reasoning about context/situations and performs gradual adaptation of data mining and visualization parameters according to the occurring situations. A prototype of the architecture is implemented and described in the paper through a real-world scenario in the area of healthcare monitoring.

Keywords

Data Stream Mining Fuzzy logic Context-aware Visualization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Pari Delir Haghighi
    • 1
  • Brett Gillick
    • 1
  • Shonali Krishnaswamy
    • 1
  • Mohamed Medhat Gaber
    • 1
  • Arkady Zaslavsky
    • 1
  1. 1.Centre for Distributed Systems and Software EngineeringMonash UniversityCaulfield EastAustralia

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