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
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Constraint-Based Rule Mining in Large, Dense Databases
Data Mining and Knowledge Discovery
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries
Data Mining and Knowledge Discovery
A Tight Upper Bound on the Number of Candidate Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On Maximal Frequent and Minimal Infrequent Sets in Binary Matrices
Annals of Mathematics and Artificial Intelligence
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical properties of transactional databases
Proceedings of the 2004 ACM symposium on Applied computing
On support thresholds in associative classification
Proceedings of the 2004 ACM symposium on Applied computing
Advances in frequent itemset mining implementations: report on FIMI'03
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Support envelopes: a technique for exploring the structure of association patterns
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Essential classification rule sets
ACM Transactions on Database Systems (TODS)
An effective and efficient algorithm for high-dimensional outlier detection
The VLDB Journal — The International Journal on Very Large Data Bases
Distribution-Based Synthetic Database Generation Techniques for Itemset Mining
IDEAS '05 Proceedings of the 9th International Database Engineering & Application Symposium
From Intent Reducts for Attribute Implications to Approximate Intent Reducts for Association Rules
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
IEEE Transactions on Knowledge and Data Engineering
ACM Computing Surveys (CSUR)
Frequent closed itemset based algorithms: a thorough structural and analytical survey
ACM SIGKDD Explorations Newsletter
Mining maximal hyperclique pattern: A hybrid search strategy
Information Sciences: an International Journal
The effect of threshold values on association rule based classification accuracy
Data & Knowledge Engineering
Using metarules to organize and group discovered association rules
Data Mining and Knowledge Discovery
Frequent Closed Sequence Mining without Candidate Maintenance
IEEE Transactions on Knowledge and Data Engineering
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
On stability of a formal concept
Annals of Mathematics and Artificial Intelligence
Towards a Finer Assessment of Extraction Contexts Sparseness
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
Redundant association rules reduction techniques
International Journal of Business Intelligence and Data Mining
A Contribution to the Use of Decision Diagrams for Loading and Mining Transaction Databases
Fundamenta Informaticae - Special issue ISMIS'05
Adequate condensed representations of patterns
Data Mining and Knowledge Discovery
Mining Frequent Closed Unordered Trees Through Natural Representations
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
A new concise representation of frequent itemsets using generators and a positive border
Knowledge and Information Systems
Top-down mining of frequent closed patterns from very high dimensional data
Information Sciences: an International Journal
Analysis of sampling techniques for association rule mining
Proceedings of the 12th International Conference on Database Theory
Size of random Galois lattices and number of closed frequent itemsets
Discrete Applied Mathematics
Data & Knowledge Engineering
Sliding window-based frequent pattern mining over data streams
Information Sciences: an International Journal
An algorithm to mine general association rules from tabular data
Information Sciences: an International Journal
An efficient algorithm for finding dense regions for mining quantitative association rules
Computers & Mathematics with Applications
Closure spaces that are not uniquely generated
Discrete Applied Mathematics - Ordinal and symbolic data analysis (OSDA 2000)
SCALE: a scalable framework for efficiently clustering transactional data
Data Mining and Knowledge Discovery
A new classification of datasets for frequent itemsets
Journal of Intelligent Information Systems
Discovering multi-label temporal patterns in sequence databases
Information Sciences: an International Journal
Using ontologies to facilitate post-processing of association rules by domain experts
Information Sciences: an International Journal
Methods for mining frequent items in data streams: an overview
Knowledge and Information Systems
Generalization of association rules through disjunction
Annals of Mathematics and Artificial Intelligence
Prince: an algorithm for generating rule bases without closure computations
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Essential patterns: a perfect cover of frequent patterns
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 the use of meta-learning for instance selection: An architecture and an experimental study
Information Sciences: an International Journal
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It is widely recognized that the performances of frequent-pattern mining algorithms are closely dependent on data being handled, i.e., sparse or dense. The same situation applies to the efficiency of concise representations of frequently occurring patterns with respect to the extraction task and the obtained compactness rates, as well as for other data mining techniques such as clustering, and for the mining algorithms of different pattern classes such as hypergraphs. In this paper, we raise a fundamental question: how can we formally define the sparseness of an arbitrary context and assess its value? As an answer, based on the framework of the succinct system of minimal generators, we present an innovative characterization of context sparseness, as well as a new sparseness measure which results from the aggregation of two complementary measures, namely the succinctness and compactness measures of each equivalence class, induced by the Galois closure operator. Experiments carried out mainly attain a finer classification of benchmark contexts and, then, confirm our viewpoint that the ''dense'' and ''sparse'' labels are not absolute.