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Annals of Computer Science and Information Systems, Volume 9

Position Papers of the 2016 Federated Conference on Computer Science and Information Systems

Clustering Validity Indices Evaluation with Regard to Semantic Homogeneity

DOI: http://dx.doi.org/10.15439/2016F371

Citation: Position Papers of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 9, pages 39 ()

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Abstract. Clustering validity indices are a methods for examining and assessing quality of data clustering results. Various studies provide thorough evaluation of their performance using both synthetic and real-world datasets. In this work, we describe various approaches to the topic of evaluation of a clustering scheme. Moreover, a new solution to a problem of selecting an appropriate clustering validity index is presented. The approach is applied to a problem of selecting an appropriate clustering validity index for a real-world task of clustering biomedical articles with usage of MeSH ontology.


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