Shortest-path kernels on graphs
2005
Conference Paper
ei
Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either computationally expensive or limited in their expressiveness. We try to overcome this problem by defining expressive graph kernels which are based on paths. As the computation of all paths and longest paths in a graph is NP-hard, we propose graph kernels based on shortest paths. These kernels are computable in polynomial time, retain expressivity and are still positive definite. In experiments on classification of graph models of proteins, our shortest-path kernels show significantly higher classification accuracy than walk-based kernels.
Author(s): | Borgwardt, KM. and Kriegel, H-P. |
Pages: | 74-81 |
Year: | 2005 |
Month: | November |
Day: | 0 |
Publisher: | IEEE Computer Society |
Department(s): | Empirische Inferenz |
Bibtex Type: | Conference Paper (inproceedings) |
DOI: | 10.1109/ICDM.2005.132 |
Event Name: | Fifth International Conference on Data Mining (ICDM 2005) |
Event Place: | Houston, TX, USA |
Address: | Los Alamitos, CA, USA |
Digital: | 0 |
ISBN: | 0-7695-2278-5 |
Links: |
Web
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BibTex @inproceedings{BorgwardtK2005, title = {Shortest-path kernels on graphs}, author = {Borgwardt, KM. and Kriegel, H-P.}, pages = {74-81}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, month = nov, year = {2005}, doi = {10.1109/ICDM.2005.132}, month_numeric = {11} } |