Journal of the ACM (JACM)
Experimental study of minimum cut algorithms
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
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
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Carpenter: finding closed patterns in long biological datasets
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
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
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Coherent closed quasi-clique discovery from large dense graph databases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Out-of-core coherent closed quasi-clique mining from large dense graph databases
ACM Transactions on Database Systems (TODS)
Netprobe: a fast and scalable system for fraud detection in online auction networks
Proceedings of the 16th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
CSV: visualizing and mining cohesive subgraphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
SkyGraph: an algorithm for important subgraph discovery in relational graphs
Data Mining and Knowledge Discovery
Effective Pruning Techniques for Mining Quasi-Cliques
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
FOGGER: an algorithm for graph generator discovery
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Multi-way set enumeration in real-valued tensors
Proceedings of the 2nd Workshop on Data Mining using Matrices and Tensors
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
gPrune: a constraint pushing framework for graph pattern mining
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
TGP: mining top-K frequent closed graph pattern without minimum support
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Discovering highly reliable subgraphs in uncertain graphs
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Using and learning semantics in frequent subgraph mining
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Finding maximal k-edge-connected subgraphs from a large graph
Proceedings of the 15th International Conference on Extending Database Technology
Efficiently computing k-edge connected components via graph decomposition
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
A multiobjective evolutionary programming framework for graph-based data mining
Information Sciences: an International Journal
MFMS: maximal frequent module set mining from multiple human gene expression data sets
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics
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Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identifying highly associated groups and clusters. In this paper, we investigate the issues of mining closed frequent graphs with connectivity constraints in massive relational graphs where each graph has around 10K nodes and 1M edges. We adopt the concept of edge connectivity and apply the results from graph theory, to speed up the mining process. Two approaches are developed to handle different mining requests: CloseCut, a pattern-growth approach, and splat, a pattern-reduction approach. We have applied these methods in biological datasets and found the discovered patterns interesting.