Graph-based data mining
- 1 March 2000
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Intelligent Systems and their Applications
- Vol. 15 (2), 32-41
- https://doi.org/10.1109/5254.850825
Abstract
Using databases represented as graphs, the Subdue system performs two key data-mining techniques: unsupervised pattern discovery and supervised concept learning from examples. Applications to large structural databases demonstrate Subdue's scalability and effectiveness.Keywords
This publication has 9 references indexed in Scilit:
- Exploiting parallelism in a structural scientific discovery system to improve scalabilityJournal of the American Society for Information Science, 1999
- An empirical study of domain knowledge and its benefits to substructure discoveryIEEE Transactions on Knowledge and Data Engineering, 1997
- Scalable discovery of informative structural concepts using domain knowledgeIEEE Expert, 1996
- Machine discovery of protein motifsMachine Learning, 1995
- Machine learning approaches to gene recognitionIEEE Expert, 1994
- Conjecturing hidden entities by means of simplicity and conservation laws: Machine discovery in chemistryArtificial Intelligence, 1994
- Substructure Discovery Using Minimum Description Length and Background KnowledgeJournal of Artificial Intelligence Research, 1994
- Efficient top-down induction of logic programsACM SIGART Bulletin, 1994
- Knowledge acquisition via incremental conceptual clusteringMachine Learning, 1987