Publicación:
A comparison of extrinsic clustering evaluation metrics based on formal constraints

dc.contributor.authorArtiles, Javier
dc.contributor.authorVerdejo, Felisa
dc.contributor.authorAmigo Cabrera, Enrique
dc.contributor.authorGonzalo Arroyo, Julio Antonio
dc.date.accessioned2024-05-21T13:03:35Z
dc.date.available2024-05-21T13:03:35Z
dc.date.issued2009-05-11
dc.description.abstractThere is a wide set of evaluation metrics available to compare the quality of text clustering algorithms. In this article, we define a few intuitive formal constraints on such metrics which shed light on which aspects of the quality of a clustering are captured by different metric families. These formal constraints are validated in an experiment involving human assessments, and compared with other constraints proposed in the literature. Our analysis of a wide range of metrics shows that only BCubed satisfies all formal constraints. We also extend the analysis to the problem of overlapping clustering, where items can simultaneously belong to more than one cluster. As Bcubed cannot be directly applied to this task, we propose a modified version of Bcubed that avoids the problems found with other metrics.en
dc.identifier.urihttps://hdl.handle.net/20.500.14468/19990
dc.language.isoen
dc.publisherSpringer
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentLenguajes y Sistemas Informáticos
dc.relation.projectidinfo:eu-repo/grantAgreement/S2009/TIC-1542
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.titleA comparison of extrinsic clustering evaluation metrics based on formal constraintses
dc.typeconference proceedingsen
dc.typeactas de congresoes
dspace.entity.typePublication
relation.isAuthorOfPublicationf96c6e59-3a7a-4b0c-9b10-deec22f8c06b
relation.isAuthorOfPublication0e0d6c85-2d8e-4fb3-9640-8ad17e875fcc
relation.isAuthorOfPublication.latestForDiscoveryf96c6e59-3a7a-4b0c-9b10-deec22f8c06b
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