Multidimensional data clustering utilizing hybrid search strategies
Pattern Recognition
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
ACM Computing Surveys (CSUR)
Partitioning-based clustering for Web document categorization
Decision Support Systems - Special issue on WITS '97
A vector space model for automatic indexing
Communications of the ACM
Principal Direction Divisive Partitioning
Data Mining and Knowledge Discovery
Performance Evaluation of Some Clustering Algorithms and Validity Indices
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Cluster ensembles: a knowledge reuse framework for combining partitionings
Eighteenth national conference on Artificial intelligence
IEEE Transactions on Knowledge and Data Engineering
Document Clustering Using Locality Preserving Indexing
IEEE Transactions on Knowledge and Data Engineering
Robust growing neural gas algorithm with application in cluster analysis
Neural Networks - 2004 Special issue: New developments in self-organizing systems
A parallel hybrid web document clustering algorithm and its performance study
The Journal of Supercomputing - Special issue: Parallel and distributed processing and applications
Cumulative Voting Consensus Method for Partitions with Variable Number of Clusters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering with r-regular graphs
Pattern Recognition
Robust cluster validity indexes
Pattern Recognition
A fast k-means clustering algorithm using cluster center displacement
Pattern Recognition
Enhanced bisecting k-means clustering using intermediate cooperation
Pattern Recognition
Incremental spectral clustering by efficiently updating the eigen-system
Pattern Recognition
Enhanced neural gas network for prototype-based clustering
Pattern Recognition
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Fast agglomerative clustering using information of k-nearest neighbors
Pattern Recognition
Estimation of the number of clusters using heterogeneous multiple classifier system
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Cooperative clustering for software modularization
Journal of Systems and Software
A Fast Multiclass Classification Algorithm Based on Cooperative Clustering
Neural Processing Letters
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Data clustering plays an important role in many disciplines, including data mining, machine learning, bioinformatics, pattern recognition, and other fields, where there is a need to learn the inherent grouping structure of data in an unsupervised manner. There are many clustering approaches proposed in the literature with different quality/complexity tradeoffs. Each clustering algorithm works on its domain space with no optimum solution for all datasets of different properties, sizes, structures, and distributions. In this paper, a novel cooperative clustering (CC) model is presented. It involves cooperation among multiple clustering techniques for the goal of increasing the homogeneity of objects within the clusters. The CC model is capable of handling datasets with different properties by developing two data structures, a histogram representation of the pair-wise similarities and a cooperative contingency graph. The two data structures are designed to find the matching sub-clusters between different clusterings and to obtain the final set of clusters through a coherent merging process. The cooperative model is consistent and scalable in terms of the number of adopted clustering approaches. Experimental results show that the cooperative clustering model outperforms the individual clustering algorithms over a number of gene expression and text documents datasets.