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» Structure feature selection for graph classification
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ICIAP
2009
ACM
13 years 6 months ago
Tree Covering within a Graph Kernel Framework for Shape Classification
Abstract. Shape classification using graphs and skeletons usually involves edition processes in order to reduce the influence of structural noise. However, edition distances can no...
François-Xavier Dupé, Luc Brun
ICPR
2008
IEEE
14 years 9 months ago
Combining content and structure similarity for XML document classification using composite SVM kernels
Combination of structure and content features is necessary for effective retrieval and classification of XML documents. Composite kernels provide a way for fusion of content and s...
Pabitra Mitra, Saptarshi Ghosh
IJBRA
2007
97views more  IJBRA 2007»
13 years 8 months ago
Structural Risk Minimisation based gene expression profiling analysis
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
Xue-wen Chen, Byron Gerlach, Dechang Chen, ZhenQiu...
SOCIALCOM
2010
13 years 6 months ago
Using Text Analysis to Understand the Structure and Dynamics of the World Wide Web as a Multi-Relational Graph
A representation of the World Wide Web as a directed graph, with vertices representing web pages and edges representing hypertext links, underpins the algorithms used by web search...
Harish Sethu, Alexander Yates
ICDM
2006
IEEE
166views Data Mining» more  ICDM 2006»
14 years 2 months ago
Mining Generalized Graph Patterns Based on User Examples
There has been a lot of recent interest in mining patterns from graphs. Often, the exact structure of the patterns of interest is not known. This happens, for example, when molecu...
Pavel Dmitriev, Carl Lagoze