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Lecturer(s)
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Kašparová Miloslava, Ing. Ph.D.
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Course content
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Data, information, knowledge. Data sources. Data pre-processing. Selection and transformation of variables. Modelling (classification and prediction methods). Processing, evaluation, verification and model implementation. Text Mining and Web Mining.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Work with text (with textbook, with book), Skills training
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Learning outcomes
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The aim of the course is to provide information on modern searching technologies and methods of knowledge extraction. Attention will be paid to basic principles of knowledge extraction in internal and external information sources (databases, text documents, web). Emphasis is also put on visual analysis.
Students will be able to work with sources of information and will have an awareness of the tools and methods used for knowledge extraction.
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Prerequisites
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no
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Assessment methods and criteria
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Written examination, Home assignment evaluation, Discussion
Assignment is conditional to attendance at seminars and the completion of set work. Examination: written form.
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Recommended literature
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Berka, Petr. Dobývání znalostí z databází. Praha: Academia, 2003. ISBN 80-200-1062-9.
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Coderre, D. Computer Aided Fraud Prevention and Detection: A Step by Step Guide. New Jersey, 2009. ISBN 0470392436.
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Ducháčková, Eva. Principy pojištění a pojišťovnictví. Praha: Ekopress, 2009. ISBN 978-80-86929-51-4.
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Meloun, Milan. Kompendium statistického zpracování dat : metody a řešené úlohy včetně CD. Praha: Academia, 2002. ISBN 80-200-1008-4.
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Petr, P. Data Mining (skripta). Pardubice: Univerzita Pardubice, 2006.
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Rud, Olivia Parr. Data mining : praktický průvodce dolováním dat pro efektivní prodej, cílený marketing a podporu zákazníků (CRM). Praha: Computer Press, 2001. ISBN 80-7226-577-6.
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Sklenák, Vilém. Data, informace, znalosti a Internet. V Praze: C.H. Beck, 2001. ISBN 80-7179-409-0.
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