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JCP
2008
171views more  JCP 2008»
13 years 7 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
ICDM
2008
IEEE
106views Data Mining» more  ICDM 2008»
14 years 2 months ago
Metropolis Algorithms for Representative Subgraph Sampling
While data mining in chemoinformatics studied graph data with dozens of nodes, systems biology and the Internet are now generating graph data with thousands and millions of nodes....
Christian Hübler, Hans-Peter Kriegel, Karsten...
ICML
2010
IEEE
13 years 8 months ago
Fast Neighborhood Subgraph Pairwise Distance Kernel
We introduce a novel graph kernel called the Neighborhood Subgraph Pairwise Distance Kernel. The kernel decomposes a graph into all pairs of neighborhood subgraphs of small radius...
Fabrizio Costa, Kurt De Grave
ICPR
2004
IEEE
14 years 8 months ago
Structural Graph Matching With Polynomial Bounds On Memory and on Worst-Case Effort
A new method of structural graph matching is introduced and compared against an existing method and against the maximum common subgraph. The method is approximate with polynomial ...
Fred W. DePiero
MLG
2007
Springer
14 years 1 months ago
Support Computation for Mining Frequent Subgraphs in a Single Graph
—Defining the support (or frequency) of a subgraph is trivial when a database of graphs is given: it is simply the number of graphs in the database that contain the subgraph. Ho...
Mathias Fiedler, Christian Borgelt