|
|
Using system LISp-Miner for large real data
Hrnčíř, Jan ; Rauch, Jan (advisor) ; Chudán, David (referee)
This dissertation thesis describes an advanced method of knowledge discovery in databases (KDD), implemented in system LISp-Miner. The goal is to show the possibilities of coordinated use of analytical tools and complex procedures GUHA in this system. The thesis uses methodology CRISP-DM, which is firstly described and work is proceeded using this methodology in the following sections. The author firstly introduces readers domain area and then the data itself, which are processed to the analysis needs. Analytical questions that are answered at, are drawn from the literature, which is focused on domain area. The work should be used as a guide to LISp-Miner users, using analytical tools and procedures GUHA is therefore described the easiest way to understand.
|
|
|
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.
|
|
|
Use of data mining techniques for open data
Prokůpek, Miroslav ; Rauch, Jan (advisor) ; Chudán, David (referee)
This diploma thesis examines applications of datamining methods to open data. It is realized by solving analytical questions using the LISp-Miner system. Analytical questions are examined in data from The Czech Trade Inspection Authority from the perspective of the data owner. Procedure used to solve analytical questions is 4ft-Miner. There are presented and resolved four analytical questions, which are the results of the work. Work includes a detailed description of the transformation of the relational database into a format suitable for data mining. A detailed description of the data is also included. The theoretical part deals with the GUHA method and CRISP-DM methodology.
|
|
|
Application of KDD on the data of plastic surgery clients
Šotlík, Jakub ; Rauch, Jan (advisor) ; Tomášek, David (referee)
The main objective of my thesis is to analyze data about clients of plastic and aesthetic surgery with methods and tools of the Knowledge Discovery in Databases and to find as many useful knowledge as possible from the data's owner view (the knowledge consists of verbal rules expressing relationships between two entities). Found knowledge will be presented in SEWEBAR system. Elaboration of my work is in accordance with CRISP-DM methodology that is used for the Knowledge Discovery in Databases. Analytical questions will be solved by LISp-Miner software that uses analytical procedure 4ft-Miner of the GUHA method. Found relationships will be presented in SEWEBAR system and some interesting relationships will be presented in this work. The main purpose of the thesis is to find useful knowledge of plastic and aesthetic surgery branch from both business and medical view. From medical point of view the work finds knowledge about medical and psychological status of clients. From business point of view the work finds knowledge for management. The thesis is structured to correspond with CRISP-DM methodology where every phase of methodology has one chapter. There is result of every phase described in every chapter together with the description of my work on phase.
|
guest ::
