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FIT-ZZNAcad. year: 2013/2014
Basic concepts concerning knowledge discovery in data, relation of knowledge discovery and data mining. Data sources for knowledge discovery. Principles and techniques of data preprocessing for mining. Systems for knowledge discovery in data, data mining query languages. Data mining techniques association rules, classification and prediction, clustering. Mining unconventional data - data streams, time series and sequences, graphs, spatial and spatio-temporal data, multimedia. Text and web mining. Working-out a data mining project by means of an available data mining tool.
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branch MBS , 0 year of study, winter semester, compulsory-optionalbranch MIN , 2 year of study, winter semester, compulsorybranch MIS , 2 year of study, winter semester, compulsory-optionalbranch MMI , 0 year of study, winter semester, electivebranch MMM , 0 year of study, winter semester, electivebranch MPV , 1 year of study, winter semester, compulsory-optionalbranch MBI , 2 year of study, winter semester, compulsorybranch MGM , 2 year of study, winter semester, electivebranch MSK , 2 year of study, winter semester, compulsory-optional
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