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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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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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Utilization of Multiple Level Association Rules in an e-Shop
Králík, Michael ; Šebek, Michal (referee) ; Bartík, Vladimír (advisor)
This thesis deals with design and implementation of a complete information system for the needs of electronic shop, where multiple level association rules will be used for data mining. The information system will include warehouse management, automated order processing, payment management, tax records and display various statistics. Technologies such as HTML, Latte, CSS, JavaScript, Nette Framework, PHP and MySQL were used to implement this system.
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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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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.
|
|
|
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.
|
|
|
Utilization of Multiple Level Association Rules in an e-Shop
Králík, Michael ; Šebek, Michal (referee) ; Bartík, Vladimír (advisor)
This thesis deals with design and implementation of a complete information system for the needs of electronic shop, where multiple level association rules will be used for data mining. The information system will include warehouse management, automated order processing, payment management, tax records and display various statistics. Technologies such as HTML, Latte, CSS, JavaScript, Nette Framework, PHP and MySQL were used to implement this system.
|
|
|
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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