Mining outliers in rule knowledge bases - clustering based methods

Agnieszka Nowak-Brzezińska

Abstract


The paper presents the problem of outlier detection in the rule knowledge bases. Unusual (rare) rules, regarded here as the deviation, should be the subject of analysis experts and knowledge engineers because they can influence the efficiency of inference in decision support systems. The author presents a different approach in finding outliers in the structure of rules’ clusters. The experiments with their results are also presented in the paper.

Keywords


outliers; cluster analysis; rules knowledge bases; efficiency

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References


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DOI: http://dx.doi.org/10.21936/si2013_v34.n2A.33