Algorithms for clustering data
Algorithms for clustering data
ROCK: a robust clustering algorithm for categorical attributes
Information Systems
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Principles of data mining
Model selection for probabilistic clustering using cross-validatedlikelihood
Statistics and Computing
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Data Clustering Using Evidence Accumulation
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Clustering with Qualitative Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Correlation Clustering: maximizing agreements via semidefinite programming
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Machine Learning
Combining multiple clustering systems
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Aggregating inconsistent information: ranking and clustering
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Correlation clustering in general weighted graphs
Theoretical Computer Science - Approximation and online algorithms
Using Global Optimization to Explore Multiple Solutions of Clustering Problems
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Robust Clustering by Aggregation and Intersection Methods
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Solution stability in linear programming relaxations: graph partitioning and unsupervised learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Heterogeneous source consensus learning via decision propagation and negotiation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Interactive Visualization Tools for Meta-Clustering
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
Metaclustering and Consensus Algorithms for Interactive Data Analysis and Validation
WILF '09 Proceedings of the 8th International Workshop on Fuzzy Logic and Applications
Deterministic Pivoting Algorithms for Constrained Ranking and Clustering Problems
Mathematics of Operations Research
Bounding and comparing methods for correlation clustering beyond ILP
ILP '09 Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing
Multiple data structure discovery through global optimisation, meta clustering and consensus methods
International Journal of Knowledge Engineering and Soft Data Paradigms
Fragment-based clustering ensembles
Proceedings of the 18th ACM conference on Information and knowledge management
Using Data Mining Techniques to Support the Creation of Competence Ontologies
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Global optimization, meta clustering and consensus clustering for class prediction
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Application notes: data mining in cancer research
IEEE Computational Intelligence Magazine
Improved consensus clustering via linear programming
ACSC '10 Proceedings of the Thirty-Third Australasian Conferenc on Computer Science - Volume 102
A polynomial time approximation scheme for k-consensus clustering
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Multiple clustering solutions analysis through least-squares consensus algorithms
CIBB'09 Proceedings of the 6th international conference on Computational intelligence methods for bioinformatics and biostatistics
Continuous summarization of co-evolving data in large water distribution network
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Exploring the performance limit of cluster ensemble techniques
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Towards a more discriminative and semantic visual vocabulary
Computer Vision and Image Understanding
Minimum spanning tree based split-and-merge: A hierarchical clustering method
Information Sciences: an International Journal
Advancing data clustering via projective clustering ensembles
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Beyond classical consensus clustering: The least squares approach to multiple solutions
Pattern Recognition Letters
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Clustering aggregation for improving ant based clustering
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Fitting Tree Metrics: Hierarchical Clustering and Phylogeny
SIAM Journal on Computing
Positional and confidence voting-based consensus functions for fuzzy cluster ensembles
Fuzzy Sets and Systems
Generalized Adjusted Rand Indices for cluster ensembles
Pattern Recognition
Privileged information for data clustering
Information Sciences: an International Journal
On the parameterized complexity of consensus clustering
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Cluster ensembles via weighted graph regularized nonnegative matrix factorization
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
A genetic graph-based clustering algorithm
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Routing state distance: a path-based metric for network analysis
Proceedings of the 2012 ACM conference on Internet measurement conference
Projective clustering ensembles
Data Mining and Knowledge Discovery
Triangular kernel nearest-neighbor-based clustering algorithm for discovering true clusters
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
Fast parameterless density-based clustering via random projections
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
New cluster ensemble approach to integrative biological data analysis
International Journal of Data Mining and Bioinformatics
DUET: integration of dynamic and static analyses for malware clustering with cluster ensembles
Proceedings of the 29th Annual Computer Security Applications Conference
A self-supervised framework for clustering ensemble
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
A theoretic framework of K-means-based consensus clustering
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Ensembles for unsupervised outlier detection: challenges and research questions a position paper
ACM SIGKDD Explorations Newsletter
Estimating the predominant number of clusters in a dataset
Intelligent Data Analysis
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We consider the following problem: given a set of clusterings, find a single clustering that agrees as much as possible with the input clusterings. This problem, clustering aggregation, appears naturally in various contexts. For example, clustering categorical data is an instance of the clustering aggregation problem; each categorical attribute can be viewed as a clustering of the input rows where rows are grouped together if they take the same value on that attribute. Clustering aggregation can also be used as a metaclustering method to improve the robustness of clustering by combining the output of multiple algorithms. Furthermore, the problem formulation does not require a priori information about the number of clusters; it is naturally determined by the optimization function. In this article, we give a formal statement of the clustering aggregation problem, and we propose a number of algorithms. Our algorithms make use of the connection between clustering aggregation and the problem of correlation clustering. Although the problems we consider are NP-hard, for several of our methods, we provide theoretical guarantees on the quality of the solutions. Our work provides the best deterministic approximation algorithm for the variation of the correlation clustering problem we consider. We also show how sampling can be used to scale the algorithms for large datasets. We give an extensive empirical evaluation demonstrating the usefulness of the problem and of the solutions.