Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
A Monte Carlo algorithm for fast projective clustering
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Scalable density-based distributed clustering
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Levelwise Search Algorithm for Interesting Subspace Clusters
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
LCM ver.3: collaboration of array, bitmap and prefix tree for frequent itemset mining
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
Uniform Data Sampling from a Peer-to-Peer Network
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
An Efficient Constraint-Based Closed Set Mining Algorithm
ICMLA '07 Proceedings of the Sixth International Conference on Machine Learning and Applications
Efficient mining of large maximal bicliques
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Co-clustering: A Versatile Tool for Data Analysis in Biomedical Informatics
IEEE Transactions on Information Technology in Biomedicine
Learning in parallel universes
Data Mining and Knowledge Discovery
Algorithm for low-variance biclusters to identify coregulation modules in sequencing datasets
Proceedings of the Tenth International Workshop on Data Mining in Bioinformatics
A game theoretic framework for heterogenous information network clustering
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining low-variance biclusters to discover coregulation modules in sequencing datasets
Scientific Programming - Biological Knowledge Discovery and Data Mining
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Conventional clustering algorithms group similar data points together along one dimension of a data table. Bi-clustering simultaneously clusters both dimensions of a data table. 3-clustering goes one step further and aims to concurrently cluster two data tables that share a common set of row labels, but whose column labels are distinct. Such clusters reveal the underlying connections between the elements of all three sets. We present a novel algorithm that discovers 3-clusters across vertically partitioned data. Our approach presents two new and important formulations: first we introduce the notion of a 3-cluster in partitioned data; and second we present a mathematical formulation that measures the quality of such clusters. Our algorithm discovers high quality, arbitrarily positioned, overlapping clusters, and is efficient in time. These results are exhibited in a comprehensive study on real datasets.