Incremental Spectral Clustering

  • Abdelhamid Bouchachia
  • Markus Prossegger


In the present contribution, a novel algorithm for off-line spectral clustering algorithm is introduced and an online extension is derived in order to deal with sequential data. The proposed algorithm aims at dealing with nonconvex clusters having different forms. It relies on the notion of communicability that allows to handle the contiguity of data distribution. In the second part of the paper, an incremental extension of the fuzzy c-varieties is proposed to serve as a building block of the incremental spectral clustering algorithm (ISC). Initial simulations are presented towards the end of the contribution to show the performance of the ISC algorithm.


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Institute of Informatics-SystemsUniversity of KlagenfurtKlagenfurtAustria
  2. 2.Carinthia University of Applied SciencesSpittal an der DrauAustria

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