06.11.2008, 17:00 Uhr s.t. im M5 Vortrag von Professor Dr. Horst Bunke, Universität Bern unter dem Titel Recent Developments in Graph Classification and Clustering Using Graph Embedding Kernels
Veröffentlicht Friday, 17.10.2008 11:49
Abstract: Graphs provide us with a powerful and flexible representation
formalism for pattern recognition. However, the vast majority of
pattern recognition algorithms rely on vectorial data descriptions and
cannot directly be applied to graphs. Recently a growing interest in
graph
kernel methods can be observed. Graph kernels aim at bridging the gap
between the high representational power and flexibility of graphs and
the large amount of algorithms available for object representations
based on feature vectors. In this talk we review recent work that aims
at transforming graphs into n-dimensional real vectors by means of
prototype selection and graph edit distance computation. This approach
allows one to build graph kernels in a straightforward way. With several
classification and clustering experiments we prove the robustness and
flexibility of our new method and show that this approach outperforms
other graph classification and clustering methods on several graph data
sets of diverse nature.
Angelegt am 17.10.2008 von N. N
Geändert am 17.10.2008 von N. N
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