Fast discovery of association rules
Advances in knowledge discovery and data mining
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
A condensed representation to find frequent patterns
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
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
Concise Representation of Frequent Patterns Based on Disjunction-Free Generators
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Closed Set Based Discovery of Representative Association Rules
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Why to Apply Generalized Disjunction-Free Generators Representation of Frequent Patterns?
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Dataless Transitions Between Concise Representations of Frequent Patterns
Journal of Intelligent Information Systems
Reducing borders of k-disjunction free representations of frequent patterns
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Essential classification rule sets
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Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Fast and Memory Efficient Mining of Frequent Closed Itemsets
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A Thorough Experimental Study of Datasets for Frequent Itemsets
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Data Mining and Knowledge Discovery
The implication problem for measure-based constraints
Information Systems
Discovering Synonyms Based on Frequent Termsets
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
A new concise representation of frequent itemsets using generators and a positive border
Knowledge and Information Systems
CP-summary: a concise representation for browsing frequent itemsets
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Closures of Downward Closed Representations of Frequent Patterns
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Non-Derivable Item Set and Non-Derivable Literal Set Representations of Patterns Admitting Negation
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A new classification of datasets for frequent itemsets
Journal of Intelligent Information Systems
Generating positive and negative exact rules using formal concept analysis: problems and solutions
ICFCA'08 Proceedings of the 6th international conference on Formal concept analysis
Compressed disjunction-free pattern representation versus essential pattern representation
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Mining triadic association rules from ternary relations
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Theoretical bounds on the size of condensed representations
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Generalized disjunction-free representation of frequents patterns with at most k negations
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Merge-Based computation of minimal generators
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Extraction of frequent few-overlapped monotone DNF formulas with depth-first pruning
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Tractable reasoning problems with fully-characterized association rules
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
Solving inverse frequent itemset mining with infrequency constraints via large-scale linear programs
ACM Transactions on Knowledge Discovery from Data (TKDD)
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Frequent patterns are often used for solving data mining problems. They are applied e.g. in discovery of association rules, epsiode rules, sequential patterns and clusters. Nevertheless, the number of frequent itemsets is usually huge. In the paper, we overview briefly four lossless representations of frequent itemsets proposed recently and offer a new lossless one that is based on generalized disjunction-free generators. We prove on the theoreticl basis that the new representation is more concise than three of four preceding representations. In practice it is much more concise than the fourth representation too. An algorithm retermining the new representation is proposed.