Node Similarities from Spreading Activation

  • Kilian Thiel
  • Michael R. Berthold
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7250)


In this paper we propose two methods to derive different kinds of node neighborhood based similarities in a network. The first similarity measure focuses on the overlap of direct and indirect neighbors. The second similarity compares nodes based on the structure of their possibly also very distant neighborhoods. Both similarities are derived from spreading activation patterns over time. Whereas in the first method the activation patterns are directly compared, in the second method the relative change of activation over time is compared. We applied both methods to a real world graph dataset and discuss some of the results in more detail.


Signature Similarity Activation Similarity Signature Vector Cosine Similarity Spreading Process 
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

© The Author(s) 2012 2012

Authors and Affiliations

  • Kilian Thiel
    • 1
  • Michael R. Berthold
    • 1
  1. 1.Nycomed Chair for Bioinformatics and Information Mining, Dept. of Computer and Information ScienceUniversity of KonstanzKonstanzGermany

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