Impact of Clustering Parameters on the Efficiency of the Knowledge Mining Process in Rule-based Knowledge Bases
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RIS BIB ENDNOTEPublication date: 24.03.2017
Schedae Informaticae, 2016, Volume 25, pp. 85 - 101
https://doi.org/10.4467/20838476SI.16.007.6188Authors
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.
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Information: Schedae Informaticae, 2016, Volume 25, pp. 85 - 101
Article type: Original article
Titles:
The University of Silesia, Katowice, ul. Bankowa 12 40-007 Katowice
IBS PAN, Doctoral Study, ul. Newelska 6 01-447 Warszawa, Polska
Published at: 24.03.2017
Article status: Open
Licence: None
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