Integrating association rule mining with relational database systems: alternatives and implications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
Machine Learning
IEEE Intelligent Systems
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
State of the art of graph-based data mining
ACM SIGKDD Explorations Newsletter
A framework for SQL-Based mining of large graphs on relational databases
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
An iterative MapReduce approach to frequent subgraph mining in biological datasets
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
OO-FSG: an object-oriented approach to mine frequent subgraphs
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
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Mining frequent subgraphs (FSG) is one form of graph mining for which only main memory algorithms exist currently. There are many applications in social networks, biology, computer networks, chemistry and the World Wide Web that require mining of frequent subgraphs. The focus of this paper is to apply relational database techniques to support frequent subgraph mining. Some of the computations, such as duplicate elimination, canonical labeling, and isomorphism checking are not straightforward using SQL. The contribution of this paper is to efficiently map complex computations to relational operators. Unlike the main memory counter parts of FSG, our approach addresses the most general graph representation including multiple edges between any two vertices, bi-directional edges, and cycles. Experimental evaluation of the proposed approach is also presented in the paper.