Machine Learning
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Intelligent clustering with instance-level constraints
Intelligent clustering with instance-level constraints
A probabilistic framework for semi-supervised clustering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning a Mahalanobis Metric from Equivalence Constraints
The Journal of Machine Learning Research
Leveraging aggregate constraints for deduplication
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Efficient incremental constrained clustering
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Towards effective document clustering: A constrained K-means based approach
Information Processing and Management: an International Journal
Clustering Trees with Instance Level Constraints
ECML '07 Proceedings of the 18th European conference on Machine Learning
K-Means with Large and Noisy Constraint Sets
ECML '07 Proceedings of the 18th European conference on Machine Learning
Constrained locally weighted clustering
Proceedings of the VLDB Endowment
A consensus based approach to constrained clustering of software requirements
Proceedings of the 17th ACM conference on Information and knowledge management
Data Mining and Knowledge Discovery
A Probabilistic Approach for Constrained Clustering with Topological Map
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Active Learning of Instance-Level Constraints for Semi-supervised Document Clustering
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Collaborative clustering with background knowledge
Data & Knowledge Engineering
C-DenStream: Using Domain Knowledge on a Data Stream
DS '09 Proceedings of the 12th International Conference on Discovery Science
Bagging Constraint Score for feature selection with pairwise constraints
Pattern Recognition
Value, cost, and sharing: open issues in constrained clustering
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Text document clustering with metric learning
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Density-based semi-supervised clustering
Data Mining and Knowledge Discovery
Boosting Clustering by Active Constraint Selection
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Background knowledge integration in clustering using purity indexes
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Automated constraint selection for semi-supervised clustering algorithm
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
Constraint scores for semi-supervised feature selection: A comparative study
Pattern Recognition Letters
Clustering with relative constraints
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph-based clustering with constraints
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Constraint selection for semi-supervised topological clustering
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Promotional subspace mining with EProbe framework
Proceedings of the 20th ACM international conference on Information and knowledge management
Improving constrained clustering with active query selection
Pattern Recognition
CECM: Constrained evidential C-means algorithm
Computational Statistics & Data Analysis
Using force-based graph layout for clustering of relational data
ADBIS'09 Proceedings of the 13th East European conference on Advances in Databases and Information Systems
An experimental study of constrained clustering effectiveness in presence of erroneous constraints
Information Processing and Management: an International Journal
Two approaches to understanding when constraints help clustering
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A semi-supervised incremental clustering algorithm for streaming data
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Improving document clustering using automated machine translation
Proceedings of the 21st ACM international conference on Information and knowledge management
Constrained spectral embedding for K-way data clustering
Pattern Recognition Letters
Active selection of clustering constraints: a sequential approach
Pattern Recognition
Constrained instance clustering in multi-instance multi-label learning
Pattern Recognition Letters
Machine Learning
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Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves performance, with respect to the true data labels. However, in most of these experiments, results are averaged over different randomly chosen constraint sets, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary significantly in how useful they are for constrained clustering; some constraint sets can actually decrease algorithm performance. We create two quantitative measures, informativeness and coherence, that can be used to identify useful constraint sets. We show that these measures can also help explain differences in performance for four particular constrained clustering algorithms.