The master thesis is focused on analysis of data comparability and commensurability in datasets, which are used for obtaining knowledge using methods of data mining. Data comparability is one of aspects of data quality, which is crucial for correct and applicable results from data mining tasks. The aim of the theoretical part of the thesis is to briefly describe the field of knowledqe discovery and define specifics of mining of aggregated data. Moreover, the terms of comparability and commensurability is discussed. The main part is focused on process of knowledge discovery. These findings are applied in practical part of the thesis. The main goal of this part is to define general methodology, which can be used for discovery of potential problems of data comparability in analyzed data. This methodology is based on analysis of real dataset containing daily sales of products. In conclusion, the methodology is applied on data from the field of public budgets.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:359105 |
| Date | January 2017 |
| Creators | Horáková, Linda |
| Contributors | Chudán, David, Svátek, Vojtěch |
| Publisher | Vysoká škola ekonomická v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0012 seconds