Title :
LCGMiner: levelwise closed graph pattern mining from large databases
Author :
Xu, Aihua ; Lei, Hansheng
Author_Institution :
Dept. of Comput. Sci. & Eng., State Univ. of New York, USA
Abstract :
LCGMiner (levelwise closed graph pattern miner) is proposed to improve CloseGraph (Yan and Han, 2003) in discovering frequent closed sub graphs. Frequent closed edgesets with the same extended vertexsets are expanded in pattern generation compared to one edge or one vertex in traditional methods. Experiments on synthetic datasets as well as a real NIH dataset demonstrates that our algorithm outperforms CloseGraph and gSpan.
Keywords :
data mining; graph theory; pattern recognition; very large databases; CloseGraph; LCGMiner; NIH dataset; closed edgesets; extended vertexsets; frequent closed subgraph discovery; gSpan; large databases; levelwise closed graph pattern mining; pattern generation; Computer science; Data mining; Databases; Itemsets;
Conference_Titel :
Scientific and Statistical Database Management, 2004. Proceedings. 16th International Conference on
Print_ISBN :
0-7695-2146-0
DOI :
10.1109/SSDM.2004.1311240
