Choosing a propoper metric and clustering rules in composited knowledge base efficiency

Agnieszka Nowak-Brzezińska, Alicja Wakulicz-Deja


The paper presents the results of the experiments analyzing an influence choosed similarity measure on the efficiency of rules (from composited knowledge bases) clustering. In authors oppinion. Each time when we use different measure we achieving different structure of rules’ clusters and the results of inference process.


cluster analysis; rules knowledge bases; similarity measure

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