id: 01762760
dt: j
an: 01762760
au: Günter, Simon; Bunke, Horst
ti: Self-organizing map for clustering in the graph domain.
so: Pattern Recognit. Lett. 23, No.4, 405-417 (2002).
py: 2002
pu: Elsevier Science Publishers B.V. (North-Holland), Amsterdam
la: EN
cc: 
ut: self-organizing map; pattern recognition
ci: 
li: doi:10.1016/S0167-8655(01)00173-8
ab: Summary: Self-organizing map (Som) is a flexible method that can be applied
    to various tasks in pattern recognition. However it is limited in the
    sense that it uses only pattern representations in terms of feature
    vectors. It was only recently that an extension to strings was
    proposed. In the present paper we go a step further and present a
    version of Som that works in the domain of graphs. Graphs are a
    powerful data structure that include pattern representations based on
    strings and feature vectors as special cases. After introducing the new
    method a number of experiments will be described demonstrating its
    feasibility in the context of a graph clustering task.
rv: