Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A database perspective on knowledge discovery
Communications of the ACM
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Fast discovery of association rules
Advances in knowledge discovery and data mining
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Optimization of constrained frequent set queries with 2-variable constraints
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient mining of association rules using closed itemset lattices
Information Systems
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
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
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
An Information Theoretic Approach to Rule Induction from Databases
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining Free Itemsets under Constraints
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Using Condensed Representations for Interactive Association Rule Mining
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Constraint-Based Discovery and Inductive Queries: Application to Association Rule Mining
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
A perspective on inductive databases
ACM SIGKDD Explorations Newsletter
ExAMiner: Optimized Level-wise Frequent Pattern Mining with Monotone Constraints
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Optimization of a language for data mining
Proceedings of the 2003 ACM symposium on Applied computing
DBC: a condensed representation of frequent patterns for efficient mining
Information Systems
ExAnte: A Preprocessing Method for Frequent-Pattern Mining
IEEE Intelligent Systems
On condensed representations of constrained frequent patterns
Knowledge and Information Systems
Extending the state-of-the-art of constraint-based pattern discovery
Data & Knowledge Engineering
Constraint-based concept mining and its application to microarray data analysis
Intelligent Data Analysis
Visual Analytics: A 2D-3D visualization support for human-centered rule mining
Computers and Graphics
Interactive visual exploration of association rules with rule-focusing methodology
Knowledge and Information Systems
A constraint-based querying system for exploratory pattern discovery
Information Systems
Software—Practice & Experience
Database transposition for constrained (closed) pattern mining
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Pushing constraints to detect local patterns
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Pushing tougher constraints in frequent pattern mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A relational query primitive for constraint-based pattern mining
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
A novel incremental approach to association rules mining in inductive databases
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
An efficient method for mining frequent itemsets with double constraints
Engineering Applications of Artificial Intelligence
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Levelwise algorithms (e.g., the APRIORI algorithm) have been proved effective for association rule mining from sparse data. However, in many practical applications, the computation turns to be intractable for the user-given frequency threshold and the lack of focus leads to huge collections of frequent itemsets. To tackle these problems, two promising issues have been investigated during the last four years: the efficient use of user defined constraints and the computation of condensed representations for frequent itemsets, e.g., the frequent closed sets. We show that the benefits of these two approaches can be combined into a levelwise algorithm. It can be used for the discovery of association rules in difficult cases (dense and highly-correlated data). For instance, we report an experimental validation related to the discovery of association rules with negations.