Identifying the Minimal Transversals of a Hypergraph and Related Problems
SIAM Journal on Computing
A fast algorithm for building lattices
Information Processing Letters
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Incremental Transformation of Lattices: A Key to Effective Knowledge Discovery
ICGT '02 Proceedings of the First International Conference on Graph Transformation
Concise Representations of Association Rules
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
Concept Data Analysis: Theory and Applications
Concept Data Analysis: Theory and Applications
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
IEEE Transactions on Knowledge and Data Engineering
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
On computing the minimal generator family for concept lattices and icebergs
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Yet a Faster Algorithm for Building the Hasse Diagram of a Concept Lattice
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Efficient Vertical Mining of Frequent Closures and Generators
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Mining triadic association rules from ternary relations
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Why and how knowledge discovery can be useful for solving problems with CBR
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Computing Implications with Negation from a Formal Context
Fundamenta Informaticae - Concept Lattices and Their Applications
Review: Formal Concept Analysis in knowledge processing: A survey on models and techniques
Expert Systems with Applications: An International Journal
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Frequent closures (FCIs) and generators (FGs) as well as the precedence relation on FCIs are key components in the definition of a variety of association rule bases. Although their joint computation has been studied in concept analysis, no scalable algorithm exists for the task at present. We propose here to reverse a method from the latter field using a fundamental property of hypergraph theory. The goal is to extract the precedence relation from a more common mining output, i.e. closures and generators. The resulting order computation algorithm proves to be highly efficient, benefiting from peculiarities of generator families in typical mining datasets. Due to its genericity, the new algorithm fits an arbitrary FCI/FG-miner.