TY - JOUR
TI - Impact of Clustering Parameters on the Efficiency of the Knowledge Mining Process in Rule-based Knowledge Bases
AU - Nowak-Brzezińska, Agnieszka
AU - Rybotycki, Tomasz
TI - Impact of Clustering Parameters on the Efficiency of the Knowledge Mining Process in Rule-based Knowledge Bases
AB - 
	In this work the subject of the application of clustering as a knowledge extraction method from real-world data is discussed. The authors analyze an influence of different clustering parameters on the quality of the created structure of rules clusters and the efficiency of the knowledge mining process for rules / rules clusters. The goal of the experiments was to measure the impact of clustering parameters on the efficiency of the knowledge mining process in rulebased knowledge bases denoted by the size of the created clusters or the size of the representatives. Some parameters guarantee to produce shorter/longer representatives of the created rules clusters as well as smaller/greater clusters sizes.
VL - 2016
IS - Volume 25
PY - 2017
SN - 1732-3916
C1 - 2083-8476
SP - 85
EP - 101
DO - 10.4467/20838476SI.16.007.6188
UR - https://ejournals.eu/en/journal/schedae-informaticae/article/impact-of-clustering-parameters-on-the-efficiency-of-the-knowledge-mining-process-in-rule-based-knowledge-bases
KW - rule-based knowledge bases
KW - clustering
KW - similarity
KW - visualization