A Neural Network Model for Large-Scale Stream Data Learning Using Locally Sensitive Hashing

  • Aminah Ali Siti Hajar
  • Kiminori Fukase
  • Seiichi Ozawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8226)


Recently, mining knowledge from stream data such as access logs of computer, commodity distribution data, sales data, and human lifelog have been attracting many attentions. As one of the techniques suitable for such an environment, active learning has been studied for a long time. In this work, we propose a fast learning technique for neural networks by introducing Locality Sensitive Hashing (LSH) and a local learning algorithm with LSH in RBF networks.


neural networks incremental learning stream data learning locally sensitive hashing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Aminah Ali Siti Hajar
    • 1
  • Kiminori Fukase
    • 1
  • Seiichi Ozawa
    • 1
  1. 1.Graduate School of EngineeringKobe UniversityKobeJapan

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