Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
Machine Learning
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Frequent free tree discovery in graph data
Proceedings of the 2004 ACM symposium on Applied computing
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Large scale mining of molecular fragments with wildcards
Intelligent Data Analysis
The levelwise version space algorithm and its application to molecular fragment finding
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Graph-Based Procedural Abstraction
Proceedings of the International Symposium on Code Generation and Optimization
Frequent subgraph mining on a single large graph using sampling techniques
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Knowledge hiding from tree and graph databases
Data & Knowledge Engineering
Nearly exact mining of frequent trees in large networks
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
| Hi-index | 0.00 |
Given a database of graphs, structure mining algorithms search for all substructures that satisfy constraints such as minimum frequency, minimum confidence, minimum interest and maximum frequency. In order to make frequent subgraph mining more efficient, we propose to search with steps of increasing complexity. We present the GrAph/Sequence/Tree extractiON (Gaston) tool that implements this idea by searching first for frequent paths, then frequent free trees and finally cyclic graphs. We give results on large molecular databases.