Algorithms for random generation and counting: a Markov chain approach
Algorithms for random generation and counting: a Markov chain approach
Randomized algorithms
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
Transversing itemset lattices with statistical metric pruning
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A new two-phase sampling based algorithm for discovering association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
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
Mining protein family specific residue packing patterns from protein structure graphs
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
SPIN: mining maximal frequent subgraphs from graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A quickstart in frequent structure mining can make a difference
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing itemset patterns: a profile-based approach
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining compressed frequent-pattern sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Summarizing itemset patterns using probabilistic models
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining significant graph patterns by leap search
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ORIGAMI: A Novel and Effective Approach for Mining Representative Orthogonal Graph Patterns
Statistical Analysis and Data Mining
Computing the minimum-support for mining frequent patterns
Knowledge and Information Systems
Effective and efficient itemset pattern summarization: regression-based approaches
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
An integrated, generic approach to pattern mining: data mining template library
Data Mining and Knowledge Discovery
A Randomized Approach for Approximating the Number of Frequent Sets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Metropolis Algorithms for Representative Subgraph Sampling
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Mining Large Networks with Subgraph Counting
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Analysis of sampling techniques for association rule mining
Proceedings of the 12th International Conference on Database Theory
Don't be afraid of simpler patterns
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Direct local pattern sampling by efficient two-step random procedures
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Indexing and mining topological patterns for drug discovery
Proceedings of the 15th International Conference on Extending Database Technology
Linear space direct pattern sampling using coupling from the past
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Sampling minimal frequent boolean (DNF) patterns
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph classification: a diversified discriminative feature selection approach
Proceedings of the 21st ACM international conference on Information and knowledge management
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
Mining frequent subgraphs over uncertain graph databases under probabilistic semantics
The VLDB Journal — The International Journal on Very Large Data Bases
Mining frequent graph patterns with differential privacy
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Approximate graph mining with label costs
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining discriminative subgraphs from global-state networks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Randomly sampling maximal itemsets
Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics
Frequent subgraph summarization with error control
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
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Recent interest in graph pattern mining has shifted from finding all frequent subgraphs to obtaining a small subset of frequent subgraphs that are representative, discriminative or significant. The main motivation behind that is to cope with the scalability problem that the graph mining algorithms suffer when mining databases of large graphs. Another motivation is to obtain a succinct output set that is informative and useful. In the same spirit, researchers also proposed sampling based algorithms that sample the output space of the frequent patterns to obtain representative subgraphs. In this work, we propose a generic sampling framework that is based on Metropolis-Hastings algorithm to sample the output space of frequent subgraphs. Our experiments on various sampling strategies show the versatility, utility and efficiency of the proposed sampling approach.