Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Association rules over interval data
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
Query flocks: a generalization of association-rule mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Integrating association rule mining with relational database systems: alternatives and implications
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
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Scalable Techniques for Mining Causal Structures
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Constraint-Based Rule Mining in Large, Dense Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Efficient Mining of Constrained Correlated Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient dynamic mining of constrained frequent sets
ACM Transactions on Database Systems (TODS)
Efficient closed pattern mining in the presence of tough block constraints
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Frequent Itemsets without Support Threshold: With and without Item Constraints
IEEE Transactions on Knowledge and Data Engineering
CanTree: A Tree Structure for Efficient Incremental Mining of Frequent Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Answering constraint-based mining queries on itemsets using previous materialized results
Journal of Intelligent Information Systems
CanTree: a canonical-order tree for incremental frequent-pattern mining
Knowledge and Information Systems
The discovery of association rules from tabular databases comprising nominal and ordinal attributes
Intelligent Data Analysis
INCREMENTAL EXTRACTION OF ASSOCIATION RULES IN APPLICATIVE DOMAINS
Applied Artificial Intelligence
Efficient Mining of Frequent Itemsets from Data Streams
BNCOD '08 Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge
An efficient mining of weighted frequent patterns with length decreasing support constraints
Knowledge-Based Systems
Efficient single-pass frequent pattern mining using a prefix-tree
Information Sciences: an International Journal
On pushing weight constraints deeply into frequent itemset mining
Intelligent Data Analysis
Rough Set Model for Constraint-based Multi-dimensional Association Rule Mining
Proceedings of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006
Efficient algorithms for mining constrained frequent patterns from uncertain data
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data
A tree-based approach for frequent pattern mining from uncertain data
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
FpVAT: a visual analytic tool for supporting frequent pattern mining
ACM SIGKDD Explorations Newsletter
Efficient algorithms for the mining of constrained frequent patterns from uncertain data
ACM SIGKDD Explorations Newsletter
International Journal of Intelligent Information and Database Systems
Optimization of association rules extraction through exploitation of context dependent constraints
AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
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
A new class of constraints for constrained frequent pattern mining
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Pushing constraints into data streams
Proceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
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Since its introduction, frequent-set mining has been generalized to many forms, which include constrained data mining. The use of constraints permits user focus and guidance, enables user exploration and control, and leads to effective pruning of the search space and efficient mining of frequent itemsets. In this paper, we focus on the use of succinct constraints. In particular, we propose a novel algorithm called FPS to mine frequent itemsets satisfying succinct constraints. The FPS algorithm avoids the generate-and-test paradigm by exploiting succinctness properties of the constraints in a FP-tree based framework. In terms of functionality, our algorithm is capable of handling not just the succinct aggregate constraint, but any succinct constraint in general. Moreover, it handles multiple succinct constraints. In terms of performance, our algorithm is more efficient and effective than existing FP-tree based constrained frequent-set mining algorithms.