Correlation Clustering with Overlaps

The Cluster Editing problem asks for transforming a given graph into a disjoint union of cliques by applying a minimal number of edge-editing operations. The allowed operations include addition of non-existing edges and deletion of existing ones. We study a multi-parameterized version of the problem...

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Main Author: Fakhereldine, Amin (author)
Format: masterThesis
Published: 2020
Subjects:
Online Access:http://hdl.handle.net/10725/13449
https://doi.org/10.26756/th.2022.332
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
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author Fakhereldine, Amin
author_facet Fakhereldine, Amin
author_role author
dc.creator.none.fl_str_mv Fakhereldine, Amin
dc.date.none.fl_str_mv 2020
2020-05-27
2022-04-05T11:34:13Z
2022-04-05T11:34:13Z
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/13449
https://doi.org/10.26756/th.2022.332
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Cluster analysis -- Computer programs
Cluster analysis -- Mathematical models
Lebanese American University -- Dissertations
Dissertations, Academic
Algorithms
Computer science -- Mathematics
dc.title.none.fl_str_mv Correlation Clustering with Overlaps
A Multi-parameterized Approach
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description The Cluster Editing problem asks for transforming a given graph into a disjoint union of cliques by applying a minimal number of edge-editing operations. The allowed operations include addition of non-existing edges and deletion of existing ones. We study a multi-parameterized version of the problem that limits the global number of allowed edge editing operations in the graph and the local amounts of the edge edits performed per vertex. Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. In our experimental analysis, we study the efficiency of our algorithms as well as the effectiveness of allowing vertex splitting. In particular, we show that allowing vertex splitting yields higher clustering accuracy and higher intra-cluster similarity.
eu_rights_str_mv openAccess
format masterThesis
id LAURepo_0ff34b84c61dc4d47cc00e83adcab566
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/13449
publishDate 2020
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Correlation Clustering with OverlapsA Multi-parameterized ApproachFakhereldine, AminCluster analysis -- Computer programsCluster analysis -- Mathematical modelsLebanese American University -- DissertationsDissertations, AcademicAlgorithmsComputer science -- MathematicsThe Cluster Editing problem asks for transforming a given graph into a disjoint union of cliques by applying a minimal number of edge-editing operations. The allowed operations include addition of non-existing edges and deletion of existing ones. We study a multi-parameterized version of the problem that limits the global number of allowed edge editing operations in the graph and the local amounts of the edge edits performed per vertex. Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. In our experimental analysis, we study the efficiency of our algorithms as well as the effectiveness of allowing vertex splitting. In particular, we show that allowing vertex splitting yields higher clustering accuracy and higher intra-cluster similarity.1 online resource (x, 42 leaves); col. ill.Bibliography: leaf 38-42.Lebanese American University2022-04-05T11:34:13Z2022-04-05T11:34:13Z20202020-05-27Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/13449https://doi.org/10.26756/th.2022.332http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.phpeninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/134492022-07-14T06:05:18Z
spellingShingle Correlation Clustering with Overlaps
Fakhereldine, Amin
Cluster analysis -- Computer programs
Cluster analysis -- Mathematical models
Lebanese American University -- Dissertations
Dissertations, Academic
Algorithms
Computer science -- Mathematics
status_str publishedVersion
title Correlation Clustering with Overlaps
title_full Correlation Clustering with Overlaps
title_fullStr Correlation Clustering with Overlaps
title_full_unstemmed Correlation Clustering with Overlaps
title_short Correlation Clustering with Overlaps
title_sort Correlation Clustering with Overlaps
topic Cluster analysis -- Computer programs
Cluster analysis -- Mathematical models
Lebanese American University -- Dissertations
Dissertations, Academic
Algorithms
Computer science -- Mathematics
url http://hdl.handle.net/10725/13449
https://doi.org/10.26756/th.2022.332
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php