Title
Frequent Graph Mining And Its Application To Molecular Databases
Abstract
Molecular fragment mining is a promising approach for discovering novel fragments for drugs. We investigate a method for mining fragments which consists of three phases: first, a preprocessing phase for turning molecular databases into graph databases; second, the GASTON frequent graph mining phase for mining frequent paths, free trees and cyclic graphs; and third, a postprocessing phase in which redundant frequent fragments are removed. We will devote most of our attention to the frequent graph mining phase, as this phase is computationally the most demanding, but will also look at the other phases.
Year
DOI
Venue
2004
10.1109/ICSMC.2004.1401252
2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7
Keywords
Field
DocType
data mining, frequent item sets, graphs, structures, molecules
Graph theory,Data mining,Graph,Graph database,Tree (graph theory),Computer science,Molecule mining,Theoretical computer science,Preprocessor,Redundancy (engineering),Computational complexity theory
Conference
ISSN
Citations 
PageRank 
1062-922X
19
0.97
References 
Authors
7
2
Name
Order
Citations
PageRank
Siegfried Nijssen1110359.13
Joost N. Kok21429121.49