Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Constraint-based clustering in large databases
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Clustering with Instance-level Constraints
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Scalable Clustering Algorithms with Balancing Constraints
Data Mining and Knowledge Discovery
Constrained Clustering: Advances in Algorithms, Theory, and Applications
Constrained Clustering: Advances in Algorithms, Theory, and Applications
Sorting networks and their applications
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
Data Mining and Knowledge Discovery
Constraint programming for mining n-ary patterns
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Itemset mining: A constraint programming perspective
Artificial Intelligence
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A Constraint Programming Approach for Enumerating Motifs in a Sequence
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
A constraint language for declarative pattern discovery
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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Constrained clustering - finding clusters that satisfy user-specified constraints - aims at providing more relevant clusters by adding constraints enforcing required properties. Leveraging the recent progress in declarative and constraint-based pattern mining, we propose an effective constraint-clustering approach handling a large set of constraints which are described by a generic constraint-based language. Starting from an initial solution, queries can easily be refined in order to focus on more interesting clustering solutions. We show how each constraint (and query) is encoded in SAT and solved by taking benefit from several features of SAT solvers. Experiments performed using MiniSat on several datasets from the UCI repository show the feasibility and the advantages of our approach.