The chosen aspects in inference processes in decision support systems with incomplete knowledge

Agnieszka Nowak-Brzezińska, Tomasz Jach


The authors propose to use the methods of cluster analysis (clustering) in complex decision support systems with incomplete knowledge. The paper compares using of mAHC and AHC algorithms. The problem of finding the optimal number of clusters is addressed, the experiments confirming the ability of proposed approach to inference within decision support systems with incomplete knowledge are provided.


knowledge base; clustering; cluster analysis; AHC; inference; incomplete knowledge; decision support system

Full Text:

PDF (Polski)


Nowak-Brzezińska A., Simiński R., Jach T., Xięski T.: Towards a practical approach to discover internal dependencies in rule-based knowledge bases. Rough Sets and Knowledge Technology, 2011.

Nowak-Brzezińska A., Wakulicz-Deja A.: Analiza efektywności wnioskowania w złożonych bazach wiedzy. Systemy Wspomagania Decyzji, 2007.

Jain A., Dubes R.: Algorithms for clustering data. Prentice Hall, New Jersey 1988.

Chandru V., Hooker J.: Optimization methods for logical inference. John Wiley & Sons,NewYorkl999.

Zadeh L., Kacprzyk J.: Fuzzy logic for the management of uncertainty. John Wiley & Sons,New York l992.

Pawlak Z.: Rough set approach to knowledge-based decision suport. European Journal of Operational Research, 1997, s. 48-57.

Salton G.: Automatic Information Organization and Retreival. McGraw-Hill, New York,USA 1975.

Jach T., Nowak-Brzezińska A.: Wnioskowanie w systemach z wiedzą niepełną. Studia Informatica, Vol. 32, No. 2A(96), Wydawnictwo Politechniki Śląskiej, Gliwice 2011, s.377-391.

Koronacki J., Ćwik J.: Statystyczne systemy uczące się. Exit, Warszawa 2008.

Frank A., Asuncion A.: UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA 2010,

Kaufman L., Rousseeuw P.J.: Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York 1990.

Latkowski R.: Wnioskowanie w oparciu o niekompletny opis obiektów. Praca magisterska, Wydział Matematyki, Informatyki i Mechaniki Uniwersytetu Warszawskiego, Warszawa 2001.

Myatt G.: Making Sense of Data A Practical Guide to Exploratory Data Analysis and Data Mining. John Wiley and Sons, Inc., New Jersey 2007.

Kumar V., Tan P., Steinbach M.: Introduction to Data Mining. Addison-Wesley, 2006.

Geiger D., Heckerman D.: Knowledge representation and inference in similarity networks and Bayesian multinets. Artificial Intelligence, 1996, s. 45-74.

Towell G., Shavlika J.: Knowledge-based artificial neural networks. Artificial Intelligence, 1994, s. 119-165.

Bazan J., Nguyen H. S., Nguyen S. H., Synak P., Wróblewski J.: Rough set algorithms in classification problems. Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems, 2000, s. 49-88.

Bazan J., Szczuka M., Wróblewski J.: A new version of rough set exploration system. Third International Conference - RSCTC, 2002, s. 397-404.