Competitive Online Clique Clustering

DSpace Repository

Competitive Online Clique Clustering

Show full item record

Files for download

Find Full text There are no files associated with this item.


Simple item record

Publication Article, peer reviewed scientific
Title Competitive Online Clique Clustering
Author(s) Fabijan, Aleksander ; Nilsson, Bengt J. ; Persson, Mia
Date 2013
English abstract
Clique clustering is the problem of partitioning a graph into cliques so that some objective function is optimized. In online clustering, the input graph is given one vertex at a time, and any vertices that have previously been clustered together are not allowed to be separated. The objective here is to maintain a clustering the never deviates too far in the objective function compared to the optimal solution. We give a constant competitive upper bound for online clique clustering, where the objective function is to maximize the number of edges inside the clusters. We also give almost matching upper and lower bounds on the competitive ratio for online clique clustering, where we want to minimize the number of edges between clusters. In addition, we prove that the greedy method only gives linear competitive ratio for these problems.
DOI (link to publisher's fulltext)
Publisher Springer
Host/Issue Lecture Notes in Computer Science;
Volume 7878
ISSN 0302-9743
Pages 221-233
Language eng (iso)
Subject(s) online algorithms
competitive analysis
clustering algorithms
Research Subject Categories::TECHNOLOGY
Handle (link to this page)

This item appears in the following Collection(s)

Show full item record



My Account