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
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Constraint programming for itemset mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Constrained Clustering: Advances in Algorithms, Theory, and Applications
Constrained Clustering: Advances in Algorithms, Theory, and Applications
The Chosen Few: On Identifying Valuable Patterns
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
The Journal of Machine Learning Research
A framework for pattern-based global models
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Constraint programming for mining n-ary patterns
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Krimp: mining itemsets that compress
Data Mining and Knowledge Discovery
A relational view of pattern discovery
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Evaluating pattern set mining strategies in a constraint programming framework
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Proceedings of the 2004 international conference on Local Pattern Detection
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Constrained clustering using SAT
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
MiningZinc: a modeling language for constraint-based mining
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Discovering pattern sets or global patterns is an attractive issue from the pattern mining community in order to provide useful information. By combining local patterns satisfying a joint meaning, this approach produces patterns of higher level and thus more useful for the end-user than the usual local patterns. In parallel, recent works investigating relationships between data mining and constraint programming (CP) show that the CP paradigm is a powerful framework to model and mine patterns in a declarative and generic way. We present a constraint-based language which enables us to define queries in a declarative way addressing patterns sets and global patterns. By specifying what the task is, rather than providing how the solution should be computed, it is easy to process by stepwise refinements to successfully discover global patterns. The usefulness of the approach is highlighted by several examples coming from the clustering based on associations. All primitive constraints of the language are modeled and solved using the SAT framework. We illustrate the efficiency of our approach through several experiments.