Fast discovery of association rules
Advances in knowledge discovery and data mining
Query flocks: a generalization of association-rule mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The advantages of forward thinking in generating rooted and free trees
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Proceedings: 2001 IEEE International Conference on Data Mining, 29 November - 2 December 2001, San Jose, California
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications
Data Mining and Knowledge Discovery
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
SEuS: Structure Extraction Using Summaries
DS '02 Proceedings of the 5th International Conference on Discovery Science
Who Links to Whom: Mining Linkage between Web Sites
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Stochastic models for the Web graph
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Optimal implementation of conjunctive queries in relational data bases
STOC '77 Proceedings of the ninth annual ACM symposium on Theory of computing
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
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Mining the space of graph properties
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Canonical forms for labelled trees and their applications in frequent subtree mining
Knowledge and Information Systems
Mining all frequent projection-selection queries from a relational table
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Mining frequent conjunctive queries in star schemas
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Computing Supports of Conjunctive Queries on Relational Tables with Functional Dependencies
Fundamenta Informaticae
Discovery and application of functional dependencies in conjunctive query mining
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
An efficient computation of frequent queries in a star schema
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Indexing and mining of graph database based on interconnected subgraph
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Mining frequent conjunctive queries using functional and inclusion dependencies
The VLDB Journal — The International Journal on Very Large Data Bases
Mining frequent neighborhood patterns in a large labeled graph
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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We present an algorithm for mining tree-shaped patterns in a large graph. Novel about our class of patterns is that they can contain constants, and can contain existential nodes which are not counted when determining the number of occurrences of the pattern in the graph. Our algorithm has a number of provable optimality properties, which are based on the theory of conjunctive database queries. We propose a database-oriented implementation in SQL, and report upon some initial experimental results obtained with our implementation on graph data about food webs, about protein interactions, and about citation analysis.