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Data Mining in Data Stream
Sýkora, Petr ; Chmelař, Petr (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with the data mining in data stream which represents fast developing area of information technology. The text describes common principles of data mining, explains what data stream is and shows methods for its preprocessing and algorithms for following data mining. The special attention is given to the VFDT and the CVDT algorithm. The next mentioned are the spatiotemporal data and related data mining. The second part describes the design and implementation of the application for classification over spatiotemporal data stream represented by road traffic data and following prediction of spatiotemporal events (traffic-jams). The classification is performed by the VFDT and CVFDT algorithm. The application has been tested on the data set obtained by the simulation tool SUMO.
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Datamining in MS SQL Using Incremental Algorithms
David, Lukáš ; Bartík, Vladimír (referee) ; Šebek, Michal (advisor)
This work deals with issues in data streams mining which nowadays is a very dynamic area in information technology. The thesis describes the general principles of data mining. There are also the principles of data mining in the data streams. Special attention is given to the implemented algorithm CluStream. In the practical part the data stream processing solution was designed and implemented by the MSSQL technology using the above algorithm. The functionality of the algorithm was verified using own data stream generator.
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Dynamic Definable Dashboard
Počatko, Boris ; Burget, Radek (referee) ; Šebek, Michal (advisor)
This thesis deals with the design and implementation of a dynamic user-definable dashboard. The user will be able to define conditions dynamically, which will filter out and save only the data he needs. The application will support the changing of the condition definitions and the display of the graphs after they were created. The current implementations available on the internet are usually solutions designed to fit only one type of project and are not designed to meet general guidelines for a dashboard. The dashboard is designed for a smooth cooperation with high load databases and therefore not to slow down the whole solution.
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Data Mining in Data Stream
Sýkora, Petr ; Chmelař, Petr (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with the data mining in data stream which represents fast developing area of information technology. The text describes common principles of data mining, explains what data stream is and shows methods for its preprocessing and algorithms for following data mining. The special attention is given to the VFDT and the CVDT algorithm. The next mentioned are the spatiotemporal data and related data mining. The second part describes the design and implementation of the application for classification over spatiotemporal data stream represented by road traffic data and following prediction of spatiotemporal events (traffic-jams). The classification is performed by the VFDT and CVFDT algorithm. The application has been tested on the data set obtained by the simulation tool SUMO.
|
|
|
Datamining in MS SQL Using Incremental Algorithms
David, Lukáš ; Bartík, Vladimír (referee) ; Šebek, Michal (advisor)
This work deals with issues in data streams mining which nowadays is a very dynamic area in information technology. The thesis describes the general principles of data mining. There are also the principles of data mining in the data streams. Special attention is given to the implemented algorithm CluStream. In the practical part the data stream processing solution was designed and implemented by the MSSQL technology using the above algorithm. The functionality of the algorithm was verified using own data stream generator.
|
|
|
Dynamic Definable Dashboard
Počatko, Boris ; Burget, Radek (referee) ; Šebek, Michal (advisor)
This thesis deals with the design and implementation of a dynamic user-definable dashboard. The user will be able to define conditions dynamically, which will filter out and save only the data he needs. The application will support the changing of the condition definitions and the display of the graphs after they were created. The current implementations available on the internet are usually solutions designed to fit only one type of project and are not designed to meet general guidelines for a dashboard. The dashboard is designed for a smooth cooperation with high load databases and therefore not to slow down the whole solution.
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