On The Correlation Clustering Problem : Algorithm for Correlation Clustering Problem

Language: English

Published by LAP LAMBERT Academic Publishing, 2009

3838313542 / 9783838313542

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nach der Bestellung gedruckt Neuware - Printed after ordering - We consider the correlation clustering problem which was initially introduced by Bansal, Blum, Chawla et al. Given a complete graph G on n vertices, with weights of +1 or -1 defined on the edges, we want to find a partition which maximizes the sum of the number of edges with positive weights inside the clusters plus the number of edges with negative weights between different clusters. In this thesis we present a deterministic polynomial time approximation scheme for finding such a partition. Our approach is different from the one given by Bansal, Blum, Chawla et al. as it relies on the Szemeredi's Regularity Lemma. We start by introducing the problem, then we introduce the concepts of regularity lemma and give a proof of Szemeredi's Regularity Lemma. Then we present the algorithm and the proof of the correctness of the algorithm.

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Title
On The Correlation Clustering Problem : Algorithm for Correlation Clustering Problem
Author
Sriram Penumatcha
Publisher
LAP LAMBERT Academic Publishing
Publication year
2009
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3838313542
ISBN 13
9783838313542
Item weight
113 grams
Dimensions
220x150x5 mm

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