Programmable clustering

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. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval--Clustering; I.5.3 [Pattern Recognition]: Clustering--Algorithms; F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems--Geometrical problems and computations General Terms Algorithms, Theory Keywords Clustering; First-order formula

• Type: Conference
• Year: 2006
• Where: PODS
• Authors: Sreenivas Gollapudi, Ravi Kumar, D. Sivakumar
• Keywords: Acceptable Clustering, Clustering Problems, Database, PODS 2006, Specific First-order Formulae