Visualization of medical rule-based knowledge bases

• Autorzy: Nowak-Brzezińska A. , Rybotycki T.
• Języki publikacji: EN

Abstrakty

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.

Słowa kluczowe

EN

data mining; medical knowledge bases; cluster visualization; hierarchical clustering; treemaps

PL

eksploracja danych; medyczne bazy wiedzy; wizualizacja skupień; grupowanie hierarchiczne; diagramy

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 91--98
• Opis fizyczny: Bibliogr. 11 poz., rys., tab., wykr.

Twórcy

autor

Nowak-Brzezińska A.

• Institute of Computer Science, University of Silesia, 39 Bedzińska Str., 41-200 Sosnowiec, Poland

autor

Rybotycki T.

• Institute of Computer Science, University of Silesia, 39 Bedzińska Str., 41-200 Sosnowiec, Poland

Bibliografia

• [1] BAZAN J. G., SZCZUKA M. S., WROBLEWSKI J. A new version of rough set exploration system. Rough Sets and Current Trends in Computing, 2002. Springer-Verlag, Berlin, pp. 397–404.
• [2] DUNN J. C. Well separated clusters and optimal fuzzy partitions. Journal of Cybernetica, 1974, Vol. 4. pp. 95–104.
• [3] GOWER J. C. A general coefficient of similarity and some of its properties. Biometrics, 1971, Vol. 27. International Biometric Society, Washington, pp. 857–871.
• [4] HAN J., KAMBER M., PEI J. Data mining: Concepts and techniques. 2011. Morgan Kaufmann Publishers Inc.
• [5] JAIN A. K., DUBES R. C. Algorithms for clustering data. 1988. Prentice Hall, New Jersey.
• [6] MORZY T. Eksploracja danych. metody i algorytmy. 2013. Wydawnictwo Naukowe PWN, Warszawa.
• [7] NOWAK-BRZEZINSKA A., JACH T. Wnioskowanie w systemach z wiedza niepena. Studia Informatica, 2011. Wydawnictwo Politechniki lskiej, Gliwice.
• [8] NOWAK-BRZEZINSKA A., XIESKI T. Exploratory clustering and visualization. 18th International Conference in Knowledge Based and Intelligent Information and Engineering Systems, KES 2014, Gdynia, Poland, 15-17 September 2014, 2014. pp. 1082–1091.
• [9] RYBOTYCKI T. Wizualizacja struktur hierarchicznych dla regulowych baz wiedzy. 2015. Sosnowiec.
• [10] SHNEIDERMAN B. Tree visualization with tree-maps: 2-d space-filling approach. Transactions on Graphics (TOG), 1992. Association for Computing Machinery, New York.
• [11] WETZEL K. pebbles - using circular treemaps to visualize disk usage. 2004.