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Mining Multiple Level Association Rules
Nguyenová, Thanh Lam ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with multiple level association rules mining. The aim of this work is to focus on available algorithms for mining multiple level association rules and to implement an application with a graphical user interface that will demonstrate the functionality of these algorithms. Five algorithms based on the Apriori algorithm were chosen. Experiments with each algorithm were performed using the application and the results were compared and evaluated at the end of the thesis.
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Association Rule Mining
Šabatka, Ondřej ; Stryka, Lukáš (referee) ; Bartík, Vladimír (advisor)
This bachelor's thesis is concerned with the association rule mining. The first part is devoted to the explanation of data mining technology and theory, which are necessary pre-steps for getting acquainted with association analysis. The next part focuses on the association analysis itself and explains the principals of algorithm Apriori in detail. The last part of the thesis describes the implementation and testing of algorithm Apriori in the Java programming language.
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Knowledge Discovery in Text
Smékal, Luděk ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This MSc Thesis handles with so-called data mining. Data mining is about obtaining some data or informations from databases, where these data or informations are not directly visible, but they are accessible by using special algorithms. This MSc Thesis mainly aims documents clasifying by selected method in scope of digital library. The selected method is based on sets of items called "itemsets method". This method extends Apriori algorithm application field originally designed for transaction databases processing and generation of sets of frequented items.
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Mining Multiple Level Association Rules
Nguyenová, Thanh Lam ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with multiple level association rules mining. The aim of this work is to focus on available algorithms for mining multiple level association rules and to implement an application with a graphical user interface that will demonstrate the functionality of these algorithms. Five algorithms based on the Apriori algorithm were chosen. Experiments with each algorithm were performed using the application and the results were compared and evaluated at the end of the thesis.
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Knowledge Discovery in Text
Smékal, Luděk ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This MSc Thesis handles with so-called data mining. Data mining is about obtaining some data or informations from databases, where these data or informations are not directly visible, but they are accessible by using special algorithms. This MSc Thesis mainly aims documents clasifying by selected method in scope of digital library. The selected method is based on sets of items called "itemsets method". This method extends Apriori algorithm application field originally designed for transaction databases processing and generation of sets of frequented items.
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Association Rule Mining
Šabatka, Ondřej ; Stryka, Lukáš (referee) ; Bartík, Vladimír (advisor)
This bachelor's thesis is concerned with the association rule mining. The first part is devoted to the explanation of data mining technology and theory, which are necessary pre-steps for getting acquainted with association analysis. The next part focuses on the association analysis itself and explains the principals of algorithm Apriori in detail. The last part of the thesis describes the implementation and testing of algorithm Apriori in the Java programming language.
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Implementation of SQL/MM DM for Association Rules
Škodík, Zdeněk ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This project is concerned with problems of knowledge discovery in databases, in the concrete then is concerned with an association rules, which are part of the system of data mining. By that way we try to get knowledge which we can´t find directly in the database and which can be useful. There is the description of SQL/MM DM, especially then all user-defined types given by standard for association rules as well as common types which create framework for data mining. Before the description of implementation these types, there is mentioned the instruments which are used for that - programming language PL/SQL and Oracle Data Mining support. The accuracy of implementation is verified by a sample application. In the conclusion, achieved results are evaluated and possible continuation of this work is mentioned.
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