document: A quickstart in frequent structure mining can make a difference Given a database , structure mining algorithms search for substructures that satisfy constraints such as minimum frequency , minimum confidence , minimum interest and maximum frequency . Examples of substructures include graphs , trees and paths . For these substructures many mining algorithms have been proposed . In order to make graph mining more efficient , we investigate the use of the `` quickstart principle '' , which is based on the fact that these classes of structures are contained in each other , thus allowing for the development of structure mining algorithms that split the search into steps of increasing complexity . We introduce the GrAph\/Sequence\/Tree extractiON ( Gaston ) algorithm that implements this idea by searching first for frequent paths , then frequent free trees and finally cyclic graphs . We investigate two alternatives for computing the frequency of structures and present experimental results to relate these alternatives .
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