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Online Algorithms for Graph Partitioning into Cliques

Aleksander Fabijan (2014) Online Algorithms for Graph Partitioning into Cliques. EngD thesis.

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    Clique clustering is the problem of partitioning a graph into cliques so that some objective function is optimised. In online clustering the input graph is given one vertex at a time, and vertices that have been previously clustered are not allowed to be separated. The objective is to maintain a clustering that never deviates too far from the optimal offline solution. We give a constant competitive upper bound and a strategy (Lazy) for online clique clustering, where the objective function is to maximise the number of edges inside the clusters (Max-ECP). We also give almost matching upper and lower bounds on the competitive ratio for online clique clustering, where we want to minimise the number of edges between clusters (Min-ECP). In addition, we prove that the greedy method only gives linear competitive ratio for these problems. The research result shows that the proposed constant competitive strategy performs significantly better on bigger graphs than the greedy method.

    Item Type: Thesis (EngD thesis)
    Keywords: competitive analysis, clustering, online algorithm, approximation algorithm
    Number of Pages: 44
    Language of Content: English
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Andrej Brodnik5540Mentor
    prof. dr. Bengt J. NilssonComentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=10772564)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 2628
    Date Deposited: 02 Sep 2014 16:18
    Last Modified: 26 Sep 2014 13:21
    URI: http://eprints.fri.uni-lj.si/id/eprint/2628

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