Title :
Full Perfect Extension Pruning for Frequent Graph Mining
Author :
Borgelt, Christian ; Meinl, Thorsten
Author_Institution :
Eur. Center for Soft Comput., Mieres
Abstract :
Mining graph databases for frequent subgraphs has recently developed into an area of intensive research. Its main goals are to reduce the execution time of the existing basic algorithms and to enhance their capability to find meaningful graph fragments. Here we present a method to achieve the former, namely an improvement of what we called "perfect extension pruning" in an earlier paper (Borgelt, 2004). With it the number of generated fragments and visited search tree nodes can be reduced, thus accelerating the search
Keywords :
data mining; trees (mathematics); graph mining; perfect extension pruning; search tree nodes; Acceleration; Algorithm design and analysis; Biochemical analysis; Biochemistry; Databases; Frequency; Information science; Logic programming; Tree graphs; Web mining;
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
DOI :
10.1109/ICDMW.2006.82