Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering all most specific sentences
ACM Transactions on Database Systems (TODS)
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
On Computing Condensed Frequent Pattern Bases
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Discovering Frequent Geometric Subgraphs
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Computing Frequent Graph Patterns from Semistructured Data
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Exploiting Local Similarity for Indexing Paths in Graph-Structured Data
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
State of the art of graph-based data mining
ACM SIGKDD Explorations Newsletter
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Diagonally Subgraphs Pattern Mining
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
The complexity of mining maximal frequent itemsets and maximal frequent patterns
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
SPIN: mining maximal frequent subgraphs from graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Closed and Maximal Frequent Subtrees from Databases of Labeled Rooted Trees
IEEE Transactions on Knowledge and Data Engineering
Finding Frequent Patterns in a Large Sparse Graph*
Data Mining and Knowledge Discovery
Closure-Tree: An Index Structure for Graph Queries
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A Partition-Based Approach to Graph Mining
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Coherent closed quasi-clique discovery from large dense graph databases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive Parallel Graph Mining for CMP Architectures
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
MARGIN: Maximal Frequent Subgraph Mining
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Correlation search in graph databases
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast best-effort pattern matching in large attributed graphs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
ORIGAMI: Mining Representative Orthogonal Graph Patterns
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Substructure discovery using minimum description length and background knowledge
Journal of Artificial Intelligence Research
Nearly exact mining of frequent trees in large networks
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
The complexity of mining maximal frequent subgraphs
Proceedings of the 32nd symposium on Principles of database systems
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The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set of frequent subgraphs providing ample scope for pruning. MARGIN is a maximal subgraph mining algorithm that moves among promising nodes of the search space along the “border” of the infrequent and frequent subgraphs. This drastically reduces the number of candidate patterns in the search space. The proof of correctness of the algorithm is presented. Experimental results validate the efficiency and utility of the technique proposed.