Competitive Strategies for Online Clique Clustering

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Competitive Strategies for Online Clique Clustering

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Publication Conference Paper, peer reviewed
Title Competitive Strategies for Online Clique Clustering
Author(s) Chrobak, Marek ; Dürr, Christoph ; Nilsson, Bengt J.
Date 2015
Editor(s) Widmayer, Peter; Paschos, Vangelis
English abstract
A clique clustering of a graph is a partitioning of its vertices into disjoint cliques. The quality of a clique clustering is measured by the total number of edges in its cliques. We consider the online variant of the clique clustering problem, where the vertices of the input graph arrive one at a time. At each step, the newly arrived vertex forms a singleton clique, and the algorithm can merge any existing cliques in its partitioning into larger cliques, but splitting cliques is not allowed. We give an online strategy with competitive ratio 15.645 and we prove a lower bound of 6 on the competitive ratio, improving the previous respective bounds of 31 and 2.
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Publisher Springer
Host/Issue Algorithms and Complexity : 9th International Conference, CIAC 2015, Paris, France, May 20-22, 2015 : Proceedings;
Series/Issue Lecture Notes in Computer Science;9079
ISBN 978-3-319-18172-1
Pages 101-113
Language eng (iso)
Subject(s) Clustering
Online Algorithms
Graph Cliques
Research Subject Categories::MATHEMATICS
Note 9th International Conference on Algorithms and Complexity, May 20-22 2015, Paris, France
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