A database perspective on knowledge discovery
Communications of the ACM
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
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
On Closed Constrained Frequent Pattern Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Optimizing Constraint-Based Mining by Automatically Relaxing Constraints
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Advances in Knowledge Discovery and Data Mining: 9th Pacific-Asia Conference, PAKDD 2005, Hanoi, Vietnam, May 18-20, 2005, Proceedings (Lecture Notes in ... / Lecture Notes in Artificial Intelligence)
Pushing tougher constraints in frequent pattern mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
An efficient framework for mining flexible constraints
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
The hows, whys, and whens of constraints in itemset and rule discovery
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Constraint-Based mining of fault-tolerant patterns from boolean data
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Mining constraint-based patterns using automatic relaxation
Intelligent Data Analysis
Efficient mining under rich constraints derived from various datasets
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
| Hi-index | 0.00 |
A lot of works address the mining of patterns under constraints. The search space is reduced by taking advantage of pruning conditions on patterns, typically by using anti-monotone and monotone properties. In this paper, we introduce two virtual patterns in order to automatically deduce pruning conditions from any constraint coming from the primitive-based framework which gathers a large set of varied constraints. These virtual patterns enable us to provide negative and positive pruning conditions according to the generalization and the specialization of patterns. We show that these pruning conditions are monotone or anti-monotone and can be pushed into usual constraint mining algorithms. Experiments carried on several contexts show that our proposals improve the mining.