03315ntm a22005297i 4500 000568087 CZ-PrVSE 20190720083859.0 m d cr n|||||||||| 190720s2019 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Borokshinova, Anastasia ISIS:102252 dis Complementary usage of OLAP and data mining represented by GUHA procedures eng Complementary Usage of OLAP and Data Mining Represented by GUHA Procedures / Anastasia Borokshinova 2019 ?? stran : digital, PDF soubor Vedoucí práce: David Chudán Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2019 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2019 This master thesis explores the possibilities for a complementary usage of OLAP and data mining represented by GUHA procedures. One of the main goals is to propose particular scenarios for its implementation, covering several GUHA procedures as part of data mining. Apart from this goal, the work also aims to design a general methodology helping with application of mentioned synergy. The data analysis is performed using Tableau and Lisp-Miner tools. In terms of data mining, LISp-Miner, CF-Miner, SD4ft-Miner and Ac4ft-Miner procedures are used. The whole process follows the CRISP-DM methodology. The theoretical part provides a brief description of the basic concepts and principles associated with both methods, their comparison and current research on the selected topic. The practical part demonstrates an accomplishment of the thesis’s goals. For practical implementation, Los Angeles crime data was used. The contributions of this thesis include: a proposal of scenarios covering complementary usage of CF-Miner, SD4ft-Miner and Ac4ft-Miner procedures and OLAP; a recommendation related to the usage of selected GUHA procedure in terms of these scenarios, and the design of a general methodology for an application of the mentioned synergy. Způsob přístupu: Internet znalostní a webové technologie [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas OLAP data mining CRISP-DM LISp-Miner GUHA method Business Intelligence Chudán, David js20100609002 ths Svátek, Vojtěch, 1967 prosinec 1.- mzk2004217940 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/69431/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/69431 Hlavní práce https://insis.vse.cz/zp/69431/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/69431/posudek/oponent/61512 Oponentura https://insis.vse.cz/zp/69431/podrobnosti dc:identifier NEPOSILAT VSKP vse69431 190605 69431