VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Mining closed frequent free trees in graph databases
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
PrefIndex: an efficient supergraph containment search technique
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
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Free tree, as a special graph which is connected, undirected and acyclic, is extensively used in domains such as computational biology, pattern recognition, computer networks, XML databases, etc. In this paper, we present a computationally efficient algorithm F3TM (Fast Frequent Free Tree Mining) to discover all frequent free trees in a graph database. We focus ourselves on how to reduce the cost of candidate generation and minimize the number of candidates being generated. We prove a theorem that the completeness of frequent free trees can be guaranteed by growing vertices from a limited range of vertices in a free tree. Two pruning techniques, automorphism-based pruning and pruning based on canonical mapping are proposed which significantly reduce the cost of candidate generation. We conducted experimental studies on a real application dataset and we show that our F3TM outperforms the upto- date algorithms by an order of magnitude.