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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 3–9 ()

Full text

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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