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System for Testing of Business Strategy
Lanc, Martin ; Květoňová, Šárka (referee) ; Bartík, Vladimír (advisor)
Aim of this thesis is to introduce questions about trading stocks on global stock exchange. It shows up basics ideas, which are necessary to understand the system of trading stocks, building a bussines strategy and its automatization by simple information technology techniques. In the following, there is a description of concept and implementation of business system for testing a trading strategy, which is based on historical market data analysis. The next part of this work is focused on the demonstration system and its expansion possibilities. Whole aplication is created by means of scripting language PHP and Javascript, markup language HTML, using the MySQL database system.
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Creation of Database Application and Solutions for Business Intelligence
Městka, Milan ; Kott, Josef (referee) ; Kříž, Jiří (advisor)
Theme of this master’s thesis is design of software support for business intelligence. Design is realized in cooperation with corporation ZZN Pelhřimov a.s. Introduction is focused on theoretical description of business intelligence and datamining and also on development environment in which is project designed. Corporation is characterised also in introduction. Main part contains data collecting and definition of individual modules. In conclusion of this thesis will be several types of analysis from collected data and then according to these analysis, we can draw measures to improve current state of corporation.
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Comparation of Models for Datamining
Pospíšil, Jan ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
This thesis focuses on comparing of the datamining models features depending on the different databazis topology. The objekt was to find key features that at most involve the accuracy of classification. Thesis is composed from chapters in a way that even a non-professional or even a complete laik could understand the object and could find theese thesis results useful. In the beginning the reader is beeing made familiar with all the background information about datamining and its models and algorithms, the second part denotes about the model comparison and discusses its results.
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Multi-Level Association Rule Mining
Mičulka, Václav ; Kupčík, Jan (referee) ; Hlosta, Martin (advisor)
This bachelor thesis deals with multi-level association rules mining and implementation of this functionality as a plug-in to the Microsoft Analysis Services. In the beginning, the data mining is analysed and then the thesis deals with the assosiation analysis. After the theoretical and implementation aspects, algorithms ML T2L1 and the derived algorithm for level-crossing association rule mining are analysed. Subsequently, performance testing was performed. The achieved results are summed up at the end of the thesis.
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Business Intelligence - Use of Data Mining in Business Processes
Skalický, Tomáš ; Veselý, Martin (referee) ; Kříž, Jiří (advisor)
The aim of this bachelor thesis is to get acquainted with the concept of Business Intelligence as well as with the concept of data mining and its use in the company sphere. In the introductory theoretical part I will introduce the tools of Business Intelligence and data mining methods. In the following practical part I will use the methods for analysis of provided company data. The analysis obtained can be used as a support for company decision making.
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Application of data mining methods in a graph database
FEKETE, Alexandra
This bachelor thesis deals with the area of NoSQL databases with a focus on graph databases and the application of data mining methods. The main aim is to install a specific NoSQL graph database Neo4j together with the characterization of its key features and activities and to use data mining methods above the graph database. Methods of data mining are performed and analyzed the most typical examples of data obtained from the Internet. The used query language is Cypher. The last part of this thesis is an analysis of selected data from Neo4j Sandbox with a focus on the Panama Papers in the Neo4j database. To present this example, tools as Neo4j Community Server and Cypher language are used. The results of this analysis are then evaluated for their possible further use.
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Multi-Level Association Rule Mining
Mičulka, Václav ; Kupčík, Jan (referee) ; Hlosta, Martin (advisor)
This bachelor thesis deals with multi-level association rules mining and implementation of this functionality as a plug-in to the Microsoft Analysis Services. In the beginning, the data mining is analysed and then the thesis deals with the assosiation analysis. After the theoretical and implementation aspects, algorithms ML T2L1 and the derived algorithm for level-crossing association rule mining are analysed. Subsequently, performance testing was performed. The achieved results are summed up at the end of the thesis.
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Comparation of Models for Datamining
Gabriš, Ondrej ; Stryka, Lukáš (referee) ; Burgetová, Ivana (advisor)
Increasing development of information technology causes the amount of produced data to grow continously. And so the need becomes more intensive to process the produced data fast and efficiently to discover hidden knowledge contained in the data. This thesis examines the process of knowledge discovery in data, it's particular phases, various methods for mining the data and their comparation. Models of regression, neural network and decision tree are analysed in detail. The thesis also introduces one of the leading tools for datamining the SAS Enterprise Miner and demonstrates it's practical application on data. The purpose of this thesis is comparation of models for datamining in the SAS Enterprise Miner environment, discussion of the results and analysis to determine which model is suitable for different kinds of mined data.
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Multi-Level Association Rules Module of a Data Mining System
Pospíšil, Jan ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on the problematics of implementing a multilevel association rules mining module, for existing data mining project. There are two main algorithms explained, Apriori and MLT2L1. The thesis continues with the datamining module implementation, as well as the DMSL elements design. In the final chapters deal with an example dataminig task and its result comparison as well as the whole thesis achievement description.
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Web Page Classification
Kolář, Roman ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This paper presents problem of automatic webpages classification using association rules based classifier. Classification problem is presented, as a one of datamining technique, in context of mining knowledges from text data. There are many text document classification methods presented with highlighting benefits of classification methods using association rules. The main goal of work is adjusting selected classification method for relation data and design draft of webpages classifier, which classifies pages with the aid of visual properties - independent section layout on the web page, not (only) by textual data. There is also ARC-BC classification method presented as a selected method and as one of intriguing classificators, that derives accuracy and understandableness benefits of all other methods.
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