An Immune Network for Contextual Text Data Clustering

  • Krzysztof Ciesielski
  • Sławomir T. Wierzchoń
  • Mieczysław A. Kłopotek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4163)


We present a novel approach to incremental document maps creation, which relies upon partition of a given collection of documents into a hierarchy of homogeneous groups of documents represented by different sets of terms. Further each group (defining in fact separate context) is explored by a modified version of the aiNet immune algorithm to extract its inner structure. The immune cells produced by the algorithm become reference vectors used in preparation of the final document map. Such an approach proves to be robust in terms of time and space requirements as well as the quality of the resulting clustering model.


Quantization Error Contextual Model Reference Vector Immune Network Immune Algorithm 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Krzysztof Ciesielski
    • 1
  • Sławomir T. Wierzchoń
    • 1
  • Mieczysław A. Kłopotek
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarszawaPoland

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