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Building Clusters with Lower-Bounded Sizes

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LIPIcs-ISAAC-2016-4.pdf (499.9Kb)
Date
2016
Notes
in Leibniz International Proceedings in Informatics (LIPICS), vol. 64
Dewey
Recherche opérationnelle
Sujet
Clustering; Approximation Algorithms; Complexity; Matching
JEL code
C.C4.C44
DOI
http://dx.doi.org/10.4230/LIPIcs.ISAAC.2016.148
Conference name
27th International Symposium on Algorithms and Computation, ISAAC 2016
Conference date
12-2016
Conference city
Sydney
Conference country
Australia
Book title
27th International Symposium on Algorithms and Computation, ISAAC 2016
Author
Hong, Seok-Hee
Publisher
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Publisher city
Wadern (Germany)
Year
2016
ISBN
978-3-95977-026-2
URI
https://basepub.dauphine.fr/handle/123456789/16148
Collections
  • LAMSADE : Publications
Metadata
Show full item record
Author
Abu-Khzam, Faisal N.
status unknown
Bazgan, Cristina
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Casel, Katrin
status unknown
Fernau, Henning
status unknown
Type
Communication / Conférence
Item number of pages
148:1–148:12
Abstract (EN)
Classical clustering problems search for a partition of objects into a fixed number of clusters. In many scenarios however the number of clusters is not known or necessarily fixed. Further, clusters are sometimes only considered to be of significance if they have a certain size. We discuss clustering into sets of minimum cardinality k without a fixed number of sets and present a general model for these types of problems. This general framework allows the comparison of different measures to assess the quality of a clustering. We specifically consider nine quality-measures and classify the complexity of the resulting problems with respect to k. Further, we derive some polynomial-time solvable cases for k = 2 with connections to matching-type problems which, among other graph problems, then are used to compute approximations for larger values of k.

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