Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Mining frequent closed cubes in 3D datasets
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
TRIAS--An Algorithm for Mining Iceberg Tri-Lattices
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Formal Concept Analysis: Foundations and Applications (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
Out-of-core coherent closed quasi-clique mining from large dense graph databases
ACM Transactions on Database Systems (TODS)
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
Mining frequent cross-graph quasi-cliques
ACM Transactions on Knowledge Discovery from Data (TKDD)
Closed patterns meet n-ary relations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Mining coherent subgraphs in multi-layer graphs with edge labels
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Closed and noise-tolerant patterns in n-ary relations
Data Mining and Knowledge Discovery
RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphs
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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Several algorithms, namely CubeMiner , Trias , and Data-Peeler , have been recently proposed to mine closed patterns in ternary relations. We consider here the specific context where a ternary relation denotes the value of a graph adjacency matrix at different timestamps. Then, we discuss the constraint-based extraction of patterns in such dynamic graphs. We formalize the concept of *** -contiguous closed 3-clique and we discuss the availability of a complete algorithm for mining them. It is based on a specialization of the enumeration strategy implemented in Data-Peeler . Indeed, clique relevancy can be specified by means of a conjunction of constraints which can be efficiently exploited. The added-value of our strategy is assessed on a real dataset about a public bicycle renting system. The raw data encode the relationships between the renting stations during one year. The extracted *** -contiguous closed 3-cliques are shown to be consistent with our domain knowledge on the considered city.