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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/3TEPCS5
Repositorysid.inpe.br/plutao/2019/06.10.14.29   (restricted access)
Last Update2019:06.14.10.21.50 (UTC) lattes
Metadata Repositorysid.inpe.br/plutao/2019/06.10.14.29.01
Metadata Last Update2020:01.06.11.35.23 (UTC) administrator
DOI10.1016/j.asoc.2019.105482
ISSN1568-4946
Labellattes: 0096913881679975 3 ChagasLoreSant:2019:HyHeOv
Citation KeyChagasLoreSant:2019:HyHeOv
TitleA hybrid heuristic for the overlapping cluster editing problem
Year2019
Access Date2024, May 19
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size806 KiB
2. Context
Author1 Chagas, Guilherme Oliveira
2 Lorena, Luiz Antonio Nogueira
3 Santos, Rafael Duarte Coelho dos
Resume Identifier1
2 8JMKD3MGP5W/3C9JHMQ
3 8JMKD3MGP5W/3C9JJ4N
Group1 LABAC-COCTE-INPE-MCTIC-GOV-BR
2 LABAC-COCTE-INPE-MCTIC-GOV-BR
3 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 guilherme.chagas@inpe.br
2
3 rafael.santos@inpe.br
JournalApplied Soft Computing
Volume81
Pages105482
Secondary MarkA2_INTERDISCIPLINAR A2_ENGENHARIAS_IV A2_ENGENHARIAS_III A2_CIÊNCIA_DA_COMPUTAÇÃO B1_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B1_ENGENHARIAS_II B1_BIOTECNOLOGIA
History (UTC)2019-06-10 14:29:01 :: lattes -> administrator ::
2019-06-10 14:43:22 :: administrator -> lattes :: 2019
2019-06-14 10:21:51 :: lattes -> administrator :: 2019
2020-01-06 11:35:23 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsOverlapping cluster editing
Cluster editing
Overlapping clustering
Hybrid heuristic
AbstractClustering problems are applicable to several areas of science. Approaches and algorithms are as varied as the applications. From a graph theory perspective, clustering can be generated by partitioning an input graph into a vertex-disjoint union of cliques (clusters) through addition and deletion of edges. Finding the minimum number of edges additions and deletions required to cluster data that can be represented as graphs is a well-known problem in combinatorial optimization, often referred to as cluster editing problem. However, many real-world clustering applications are characterized by overlapping clusters, that is, clusters that are non-disjoint. In these situations cluster editing cannot be applied to these problems. Literature concerning a relaxation of the cluster editing, where clusters can overlap, is scarce. In this work, we propose the overlapping cluster editing problem, a variation of the cluster editing where the goal is to partition a graph, also by editing edges, into maximal cliques that are not necessarily disjoint. In addition, we also present three slightly different versions of a hybrid heuristic to solve this problem. Each hybrid heuristic is based on coupling two metaheuristicsthat, together, generate a set of clusters; and one of three mixed-integer linear programming models, also introduced in this paper, that uses these clusters as input. The objective with the metaheuristics is to limit the solution exploration space in the models resolution, therefore reducing its computational time. Tests results show that the all proposed hybrid heuristic versions are able to generate good-quality overlapping cluster editing solutions. In particular, one version of the hybrid heuristic achieved, at a low computational cost, the best results in 51 of 112 randomly-generated graphs. Although the other two hybrid heuristic versions have harder to solve models, they obtained reasonable results in medium-sized randomly-generated graphs. In addition, the hybrid heuristic achieved good results identifying labeled overlapping clusters in a supervised data set experiment. Furthermore, we also show that, with our new problem definition, clustering a vertex in more than one cluster can reduce the edges editing cost.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > A hybrid heuristic...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target File1-s2.0-S1568494619302522-main.pdf
User Grouplattes
Reader Groupadministrator
lattes
Visibilityshown
Archiving Policydenypublisher denyfinaldraft24
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.54.04 2
sid.inpe.br/mtc-m21/2012/07.13.14.58.32 1
sid.inpe.br/bibdigital/2013/09.22.23.14 1
DisseminationWEBSCI; PORTALCAPES; COMPENDEX.
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
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