Lower bounds on paraclique density

Ronald D. Hagan; Michael A. Langston; Kai Wang

doi:10.1016/j.dam.2015.11.010

Lower bounds on paraclique density

Ronald D. Hagan, Michael A. Langston, Kai Wang

Computer Science

University of Tennessee, Knoxville

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

The scientific literature teems with clique-centric clustering strategies. In this paper we analyze one such method, the paraclique algorithm. Paraclique has found practical utility in a variety of application domains, and has been successfully employed to reduce the effects of noise. Nevertheless, its formal analysis and worst-case guarantees have remained elusive. We address this issue by deriving a series of lower bounds on paraclique densities.

Original language	English
Pages (from-to)	208-212
Number of pages	5
Journal	Discrete Applied Mathematics
Volume	204
DOIs	https://doi.org/10.1016/j.dam.2015.11.010
State	Published - May 11 2016

Scopus Subject Areas

Discrete Mathematics and Combinatorics
Applied Mathematics

Keywords

Clique
Clustering
Graph density
Paraclique

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10.1016/j.dam.2015.11.010

Cite this

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title = "Lower bounds on paraclique density",

abstract = "The scientific literature teems with clique-centric clustering strategies. In this paper we analyze one such method, the paraclique algorithm. Paraclique has found practical utility in a variety of application domains, and has been successfully employed to reduce the effects of noise. Nevertheless, its formal analysis and worst-case guarantees have remained elusive. We address this issue by deriving a series of lower bounds on paraclique densities.",

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AU - Hagan, Ronald D.

AU - Langston, Michael A.

AU - Wang, Kai

PY - 2016/5/11

Y1 - 2016/5/11

N2 - The scientific literature teems with clique-centric clustering strategies. In this paper we analyze one such method, the paraclique algorithm. Paraclique has found practical utility in a variety of application domains, and has been successfully employed to reduce the effects of noise. Nevertheless, its formal analysis and worst-case guarantees have remained elusive. We address this issue by deriving a series of lower bounds on paraclique densities.

AB - The scientific literature teems with clique-centric clustering strategies. In this paper we analyze one such method, the paraclique algorithm. Paraclique has found practical utility in a variety of application domains, and has been successfully employed to reduce the effects of noise. Nevertheless, its formal analysis and worst-case guarantees have remained elusive. We address this issue by deriving a series of lower bounds on paraclique densities.

KW - Clique

KW - Clustering

KW - Graph density

KW - Paraclique

UR - https://www.scopus.com/pages/publications/84949662442

U2 - 10.1016/j.dam.2015.11.010

DO - 10.1016/j.dam.2015.11.010

M3 - Article

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VL - 204

SP - 208

EP - 212

JO - Discrete Applied Mathematics

JF - Discrete Applied Mathematics

ER -

Lower bounds on paraclique density

Abstract

Scopus Subject Areas

Keywords

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