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Options of presentation of KDD results on Web
Koválik, Tomáš ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
This diploma thesis covers KDD analysis of data and options of presentation of KDD results on Web. The paper is divided into three main sections, which follow the whole process of this thesis. In the first section are mentioned theoretical basics needed for understanding of discussed problem. In this section are described notions data matrix and domain knowledge, concept of CRISP-DM methodology, GUHA method, system LISp-Miner and implementation of GUHA method in LISp-Miner including description of core procedures 4ft-Miner and CF-Miner. The second section is dedicated to the first goal of this paper. It briefly summarizes analysis made during pre-analysis phase. Then is described process of analysis of domain knowledge in a given data set. The third part focuses on the second goal of this thesis, which is problem of presentation of KDD results on Web. This section covers brief theoretical basis for used technologies. Then is described development of export script for automatic generation of website from results found using LISp-Miner system including description of structure of the output and recommendations for work in LISp-Miner system.
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Automation of data preprocessing using domain knowledge
Beskyba, Jan ; Šimůnek, Milan (advisor) ; Pejčoch, David (referee)
In this work we propose a solution that would help automate the part of knowledge discovery in databases. Domain knowledge has an important role in the automation process which is necessary to include into the proposed program for data preparation. In the introduction to this work, we focus on the theoretical basis of knowledge discovery of databases with an emphasis on domain knowledge. Next, we focus on the basic principles of data pre-processing and scripting language LMCL that could be part of the design of the newly established applications for automated data preparation. Subsequently, we will deal with application design for data pre-processing, which will be verified on the data the House of Commons.
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Knowledge base, analytical questions, LISp-Mner system and ADAMEK data
Kubín, Richard ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
The steps associated with the analytical question solving in terms of LISp-Miner system in ADAMEK medical data are the theme of this thesis. The operating sequence of using 4ft-Miner and SD4ft-Miner procedures in ADAMEK data together with the possibility of further use of formalized background knowledge and preparing routing for automatization of the downrighted steps are the objectiv of this thesis. The summary of the basic concepts and axioms of association rules and GUHA method is the content of the theoretical part of the thesis. Operativ part starts from CRISP-DM methodology. The operating sequence enabling searching for interesting association rules in different data, that is applied on STULONG medical data afterwards in order to get instigations for it's revision, is the produce of this thesis. Used data that come from EuroMISE are concern with cardiological patients.
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