327 search results - page 43 / 66 » A Spectral Approach to Learning Structural Variations in Gra... |
FLAIRS
2010
13 years 10 months ago
2010
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
ICDM
2003
IEEE
14 years 26 days ago
2003
IEEE
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
CIDM
2009
IEEE
13 years 11 months ago
2009
IEEE
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
GG
2008
Springer
13 years 8 months ago
2008
Springer
Graph Languages1 emerged during the seventies from the necessity to process data structures with complex interrelations. Nowadays, various variants of these languages can be found...