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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Knowledge Discovery over Data Warehouses
Pumprla, Ondřej ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This Master's thesis deals with the principles of the data mining process, especially with the mining of association rules. The theoretical apparatus of general description and principles of the data warehouse creation is set. On the basis of this theoretical knowledge, the application for the association rules mining is implemented. The application requires the data in the transactional form or the multidimensional data organized in the Star schema. The implemented algorithms for finding of the frequent patterns are Apriori and FP-tree. The system allows the variant setting of parameters for mining process. Also, the validation tests and efficiency proofs were accomplished. From the point of view of the association rules searching support, the resultant application is more applicable and robust than the existing compared systems SAS Miner and Oracle Data Miner.
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Methods for Classification of WWW Pages
Svoboda, Pavel ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
The main goal of this master's thesis was to study the main principles of classification methods. Basic principles of knowledge discovery process, data mining and using an external class CSSBox are described. Special attantion was paid to implementation of a ,,k-nearest neighbors`` classification method. The first objective of this work was to create training and testing data described by 'n' attributes. The second objective was to perform experimental analysis to determine a good value for 'k', the number of neighbors.
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Web Mining - Clustering
Rychnovský, Martin ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This work presents the topic of data mining on the web. It is focused on clustering. The aim of this project was to study the field of clustering and to implement clustering through the k-means algorithm. Then, the algorithm was tested on a dataset of text documents and on data extracted from web. This clustering method was implemented by means of Java technologies.
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Knowledge Discovery in Object Relational Databases
Chytka, Karel ; Vrážel, Dušan (referee) ; Chmelař, Petr (advisor)
The goal of this master's thesis is to acquaint with a problem of a knowledge discovery and objectrelational data classification. It summarizes problems which are connected with mining spatiotemporal data. There is described data mining kernel algorithm SVM. The second part solves classification method implementation. This method solves data mining in a Caretaker trajectory database. This thesis contains application's implementation for spatio-temporal data preprocessing, their organization in database and presentation too.
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Preprocessing Methods in Knowledge Discovery
Pokorný, Lubomír ; Lukáš, Roman (referee) ; Bartík, Vladimír (advisor)
This thesis discusses preprocessing methods in knowledge discovery. There are four methods of discretization, filling in the missing values and normalization is investigated. There is closer view on building the application which discretizate numeric atribute in database. All methods were successfully tested and the results were added.
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Mining Multiple Level Association Rules
Nachtnebl, Viktor ; Stryka, Lukáš (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery from data scope is quite a young concept but is becoming more and more popular. This bachelor's thesis is engaged in mining multiple level association rules. There are four different methods of investigation discussed. These offer an insight into the problem of concept and implementation of application. At the end we have confronted and reviewed the results of these four algorithms.
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Decision Making Support in CRM Systems
Filus, Michal ; Očenášek, Pavel (referee) ; Jirák, Ota (advisor)
The thesis deals with a decision making support in CRM systems. The goal of this thesis was to design a module for decision making support in the CRM system using Pentaho analysis tools. The theoretical part contains a description of the data warehousing and data mining with a focus on analytic operations and decision making support. It also contains brief description of CRM systems and possible application of decision making support in these systems. The practical part deals with the description of architecture of CRM system CRMminer and describes the decision making support module in this system.
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Designing a system for gaining and saving the knowledge from extensive text sources
Kružík, Martin ; Buchalcevová, Alena (advisor) ; Šedivá, Zuzana (referee)
A study deals with methods and techniques of deriving and keeping knowledge from extensive text sources as is described in chosen publications. It also concerns about possibilities of using mentioned methods in designing software application, which partially automatizes its usage and facilitates the whole human cognitive process and respects its patterns and limitations of given solution. A study also brings an user interface mock-up of an application and in the end also its software engineering design consisting of graphical and lingual description of data base, presentation and logical layer. Contribution of a study is, of couse, a design itself, for system of deriving and keeping knowledge from extensive text sources of this type is not present in the market at all.
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