On generating all maximal independent sets
Information Processing Letters
Identifying the Minimal Transversals of a Hypergraph and Related Problems
SIAM Journal on Computing
Fast discovery of association rules
Advances in knowledge discovery and data mining
Degrees of acyclicity for hypergraphs and relational database schemes
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns
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)
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on 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
Frequent subgraph mining in outerplanar graphs
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
On Generating All Maximal Acyclic Subhypergraphs with Polynomial Delay
SOFSEM '09 Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science
Frequent subgraph mining in outerplanar graphs
Data Mining and Knowledge Discovery
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The class of frequent hypergraph mining problems is introduced which includes the frequent graph mining problem class and contains also the frequent itemset mining problem. We study the computational properties of different problems belonging to this class. In particular, besides negative results, we present practically relevant problems that can be solved in incremental-polynomial time. Some of our practical algorithms are obtained by reductions to frequent graph mining and itemset mining problems. Our experimental results in the domain of citation analysis show the potential of the framework on problems that have no natural representation as an ordinary graph.