03304ntm a22005537i 4500 000128936 CZ-PrVSE 20210918200059.0 m d cr n|||||||||| 210918s2021 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Novák, Petr ISIS:125903 dis Experiment dolování asociačních pravidel nad propojenými daty veřejné správy eng Experiment with rule mining from linked government data / Petr Novák 2021 ?? stran : digital, PDF soubor Vedoucí práce: Vojtěch Svátek Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2021 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2021 Some public-sector organizations and governmental bodies are publishing their data as LOD data cubes. The interlinked nature of LOD encourages the published data cubes to be enriched with additional information available from other sources published as RDF as well. This new information in the form of binary relationships contained in these knowledge graphs can be used when mining association rules over the aggregated data, which can lead to finding relationships that cannot be found in the cubes themselves. Mining of association rules over RDF data and at the same time in their aggregated form is a not yet explored area and achieving the generation of meaningful interpretable rules that bring new knowledge is not yet a solved problem. This work explores the possibilities of enriching the RDF data cube structured by the Data Cube vocabulary with the data from general knowledge graphs and of mining such data by the AMIE algorithm or its derivatives. The findings are demonstrated in a performed experiment of mining association rules with the RDFRules framework over the data sets of the Czech Social Security Administration, Czech statistical office, Wikidata, and YAGO. Způsob přístupu: Internet znalostní a webové technologie [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Data Mining OLAP AMIE Linked Data RDF Association Rules RDFRules Svátek, Vojtěch, 1967 prosinec 1.- mzk2004217940 ths Kliegr, Tomáš ISIS:8484 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/75365/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/75365 Hlavní práce https://insis.vse.cz/zp/75365/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/75365/posudek/oponent/71890 Oponentura https://insis.vse.cz/zp/75365/priloha/22570 Přiloha k práci https://insis.vse.cz/zp/75365/podrobnosti dc:identifier NEPOSILAT VSKP vse75365 210915 75365