Combinatoral Optimization in Clustering

Boris Mirkin () and Ilya Muchnik ()
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Boris Mirkin: Rutgers University, Center for Discrete Mathematics & Theoretical Computer Science (DIMACS)
Ilya Muchnik: Rutgers University, RUTCOR and DIMACS

A chapter in Handbook of Combinatorial Optimization, 1998, pp 1007-1075 from Springer

Abstract: Abstract Clustering is a mathematical technique designed for revealing classification structures in the data collected on real-world phenomena. A cluster is a piece of data (usually, a subset of the objects considered, or a subset of the variables, or both) consisting of the entities which are much “alike”, in terms of the data, versus the other part of the data. The term itself was coined in psychology back in thirties when a heuristical technique was suggested for clustering psychological variables based on pair-wise coefficients of correlation. However, two more disciplines also should be credited for the outburst of clustering occurred in the sixties: numerical taxonomy in biology and pattern recognition in machine learning. Among relevant sources are Hartigan (1975), Jain and Dubes (1988), Mirkin (1996). Simultaneously, industrial and computational applications gave rise to graph partitioning problems which are touched below in 6.2.4.

Keywords: Minimum Span Tree; Cluster Structure; Local Search Algorithm; Very Large Scale Integrate; Cluster Criterion (search for similar items in EconPapers)
Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-0303-9_15

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DOI: 10.1007/978-1-4613-0303-9_15

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