Outlier Mining in Rule-Based Knowledge Bases

dc.contributor.authorNowak-Brzezińska, Agnieszka
dc.date.accessioned2021-07-15T12:10:47Z
dc.date.available2021-07-15T12:10:47Z
dc.date.issued2017
dc.description.abstractThis paper introduces an approach to outlier mining in the context of rule-based knowledge bases. Rules in knowledge bases are a very specific type of data representation and it is necessary to analyze them carefully, especially when they differ from each other. The goal of the paper is to analyze the influence of using different similarity measures and clustering methods on the number of outliers discovered during the mining process. The results of the experiments are presented in Section 6 in order to discuss the significance of the analyzed parameters.en_EN
dc.identifier.citationNowak-Brzezińska, A. (2017). Outlier Mining in Rule-Based Knowledge Bases. Journal of Applied Computer Science, 25(2), 7-27. https://doi.org/10.34658/jacs.2017.2.7-27
dc.identifier.doihttps://doi.org/10.34658/jacs.2017.2.7-27
dc.identifier.doi10.34658/jacs.2017.2.7-27
dc.identifier.issn1507-0360
dc.identifier.urihttp://hdl.handle.net/11652/3876
dc.identifier.urihttps://doi.org/10.34658/jacs.2017.2.7-27
dc.language.isoenen_EN
dc.page.numbers. 7-27
dc.publisherWydawnictwo Politechniki Łódzkiejpl_PL
dc.publisherLodz University of Technology Pressen_EN
dc.relation.ispartofJournal of Applied Computer Science, Vol. 25, No. 2, Wydawnictwo Politechniki Łódzkiej, Łódź 2017, ISSN 1507-0360.
dc.rightsFair use conditionen_EN
dc.rightsDla wszystkich w zakresie dozwolonego użytkupl_PL
dc.rights.licenseLUT Licenseen_EN
dc.rights.licenseLicencja PŁpl_PL
dc.subjectoutlier detectionen_EN
dc.subjectsimilarity analysisen_EN
dc.subjectclusteringen_EN
dc.subjectknowledge-based systemsen_EN
dc.subjectwykrywanie wartości odstającychpl_PL
dc.subjectanaliza podobieństwapl_PL
dc.subjectgrupowaniepl_PL
dc.subjectsystemy oparte na wiedzypl_PL
dc.titleOutlier Mining in Rule-Based Knowledge Basesen_EN
dc.typeArtykułpl_PL
dc.typeArticleen_EN

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