Name
Abstract | ||
|---|---|---|
A system based on the adaptation of the search principle used in ant colony optimization (ACO) for multiobjective graph-based data mining (GBDM) is introduced in this paper. Our multiobjective ACO algorithm is designed to retrieve the best substructures in a graph database by jointly considering two criteria, support and complexity. The experimental comparison performed with a classical GBDM method shows the good performance of the new proposal on three datasets. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15461-4_46 | ANTS Conference |
Keywords | DocType | Volume |
best substructure,graph database,ant colony optimization,multiple ant colony system,good performance,experimental comparison,classical gbdm method,multiobjective graph-based data mining,substructure discovery,search principle,new proposal,multiobjective aco algorithm,data mining | Conference | 6234 |
ISSN | ISBN | Citations |
0302-9743 | 3-642-15460-3 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oscar Cordón | 1 | 1572 | 100.75 |
| Arnaud Quirin | 2 | 168 | 13.68 |
| Rocío Romero-Záliz | 3 | 61 | 9.30 |