Filtering Order Adaptation Based on Attractor Selection for Data Broadcasting System

  • Shinya Kitajima
  • Takahiro Hara
  • Tsutomu Terada
  • Shojiro Nishio
Part of the Springer Optimization and Its Applications book series (SOIA, volume 41)


Recent spread of different data broadcasting services leads to provide enormous and various heterogeneous data. Since data that a client needs are a part of them, there has been an increasing interest in information filtering techniques where a client automatically chooses and stores the necessary data. Generally, when a client performs filtering, it applies some filters sequentially, and the time required for filtering changes according to the order of filters. On the other hand, in recent years, there have been many studies about attractor selection which is an autonomous parameter control technique based on the knowledge from living organisms. In this chapter, in order to reduce the load for filtering, we propose novel methods which adaptively change the order of filters according to the change in broadcast contents. These methods adaptively decide the control parameters for filtering by using attractor selection.


Genetic Algorithm Data Item Mobile Client Random Term Calculation Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Shinya Kitajima
    • 1
  • Takahiro Hara
    • 1
  • Tsutomu Terada
    • 2
  • Shojiro Nishio
    • 1
  1. 1.Dept. of Multimedia Eng., Grad. School of Information Science and TechnologyOsaka UniversityOsakaJapan
  2. 2.Dept. of Electrical and Electronics Eng., Grad. School of Science and TechnologyKobe UniversityKobeJapan

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