Efficient mining of association rules using closed itemset lattices
Information Systems
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Mining All Non-derivable Frequent Itemsets
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Non-Redundant Association Rules
Data Mining and Knowledge Discovery
Relative risk and odds ratio: a data mining perspective
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
IEEE Transactions on Knowledge and Data Engineering
Minimum description length principle: generators are preferable to closed patterns
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Succinct system of minimal generators: a thorough study, limitations and new definitions
CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Generic association rule bases: are they so succinct?
CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Prince: an algorithm for generating rule bases without closure computations
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Mining succinct systems of minimal generators of formal concepts
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
On computing the minimal generator family for concept lattices and icebergs
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Uncovering and reducing hidden combinatorics in guigues-duquenne bases
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
ACM SIGKDD Explorations Newsletter
Mining triadic association rules from ternary relations
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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Minimal generators (MGs), aka minimal keys, play an important role in many theoretical and practical problem settings involving closure systems that originate in graph theory, relational database design, data mining, etc. As minima of the equivalence classes associated to closures, MGs underlie many compressed representations: For instance, they form premises in canonical implication/ association rules - with closures as conclusions - that losslessly represent the entire rule family of a closure system. However, MGs often show an intra-class combinatorial redundancy that makes an exhaustive storage and use impractical. In this respect, the succinct system of minimal generators (SSMG) recently introduced by Dong et al. is a first step towards a lossless reduction of this redundancy. However, as shown elsewhere, some of the claims about SSMG, e.g., its invariant size and lossless nature, do not hold. As a remedy, we propose here a new succinct family which restores the losslessness by adding few further elements to the SSMG core, while theoretically grounding the whole. Computing means for the new family are presented together with the empirical evidences about its relative size w.r.t. the entire MG family and similar structures from the literature.