A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2009; you can also visit the original URL.
The file type is application/pdf
.
Structure feature selection for graph classification
2008
Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining and machine learning community. Towards building highly accurate classification models for graph data, here we present an efficient graph feature selection method. In our method, we use frequent subgraphs as features for graph classification. Different from existing methods, we consider the spatial distribution of the
doi:10.1145/1458082.1458212
dblp:conf/cikm/FeiH08
fatcat:p2hs75zunrayfajkunyn6fe7je