Wyniki wyszukiwania - BazTech

1

Eksploracja medycznych regułowych baz wiedzy

Nowak-Brzezińska A., Rybotycki T.

Studia Informatica

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2016

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Vol. 37, nr 1

149--162

PL

Celem pracy jest eksploracja (grupowanie i wizualizacja) medycznych regułowych baz wiedzy. W artykule opisano narzędzie CluVis, zaimplementowane przez autorów, pozwalające analizować (grupować przy użyciu hierarchicznej analizy skupień) reguły i wizualizować (przy użyciu tzw. map prostokątów) ich skupienia. W ramach eksperymentów przeanalizowano wpływ miar podobieństwa wewnątrz- i międzygrupowego, metod wizualizacji, a także miary jakości skupień na wyniki eksploracji (wykrycie tendencji, nietypowości w danych).

EN

In this work the topic of applying clustering as a knowledge extraction method from real-world medical data is discussed. The authors propose hierarchical clustering method and visualization techniques for knowledge base representation in the context of medical knowledge bases for which data mining methods are success-fully employed and may resolve different problems. What is more, the authors analyze the impact of different clustering parameters on the result of searching through such structure.

2

Impact of Clustering Parameters on the Efficiency of the Knowledge Mining Process in Rule-based Knowledge Bases

Nowak-Brzezińska A., Rybotycki T.

Schedae Informaticae

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2016

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Vol. 25

85--101

EN

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.

3

Visualization of medical rule-based knowledge bases

Nowak-Brzezińska A., Rybotycki T.

Journal of Medical Informatics & Technologies

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2015

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Vol. 24

91--98

EN

In this work the topic of applying clustering as a knowledge extraction method from real-world data is discussed. The authors propose hierarchical clustering method and visualization technique for knowledge base representation in the context of medical knowledge bases for which data mining techniques are successfully employed and may resolve different problems. What is more, the authors analyze the impact of different clustering parameters on the result of searching through such a structure. Particular attention was also given to the problem of cluster visualization. Authors review selected, two-dimensional approaches, stating their advantages and drawbacks in the context of representing complex cluster structures.