Self-Organizing Maps
Information Retrieval
Clustering Algorithms
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Semi-supervised Clustering by Seeding
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Intelligent clustering with instance-level constraints
Intelligent clustering with instance-level constraints
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Combining Multiple Clusterings Using Evidence Accumulation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Clustering Ensembles: Models of Consensus and Weak Partitions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cumulative Voting Consensus Method for Partitions with Variable Number of Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECML '07 Proceedings of the 18th European conference on Machine Learning
A consensus based approach to constrained clustering of software requirements
Proceedings of the 17th ACM conference on Information and knowledge management
Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques
Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques
Semi-supervised fuzzy clustering: A kernel-based approach
Knowledge-Based Systems
An Evidence Accumulation Approach to Constrained Clustering Combination
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Developing a group decision support system based on fuzzy information axiom
Knowledge-Based Systems
Decider: A fuzzy multi-criteria group decision support system
Knowledge-Based Systems
Knowledge-Based Systems
Swarm Intelligence in Data Mining
Swarm Intelligence in Data Mining
Data clustering with size constraints
Knowledge-Based Systems
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Privacy-preserving SOM-based recommendations on horizontally distributed data
Knowledge-Based Systems
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Data mining processes data from different perspectives into useful knowledge, and becomes an important component in designing intelligent decision support systems (IDSS). Clustering is an effective method to discover natural structures of data objects in data mining. Both clustering ensemble and semi-supervised clustering techniques have been emerged to improve the clustering performance of unsupervised clustering algorithms. Cop-Kmeans is a K-means variant that incorporates background knowledge in the form of pairwise constraints. However, there exists a constraint violation in Cop-Kmeans. This paper proposes an improved Cop-Kmeans (ICop-Kmeans) algorithm to solve the constraint violation of Cop-Kmeans. The certainty of objects is computed to obtain a better assignment order of objects by the weighted co-association. The paper proposes a new constrained self-organizing map (SOM) to combine multiple semi-supervised clustering solutions for further enhancing the performance of ICop-Kmeans. The proposed methods effectively improve the clustering results from the validated experiments and the quality of complex decisions in IDSS.