Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Aggregating inconsistent information: ranking and clustering
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Approximation algorithms for co-clustering
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Clustering under approximation stability
Journal of the ACM (JACM)
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We initiate a novel study of clustering problems. Rather than specifying an explicit objective function to optimize, our framework allows the user of clustering algorithm to specify, via a first-order formula, what constitutes an acceptable clustering to them. While the resulting genre of problems includes, in general, NP-complete problems, we highlight three specific first-order formulae, and provide efficient algorithms for the resulting clustering problems.