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Knowledge Discovery from Web Logs
Valaštín, Samuel ; Rychlý, Marek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with the problem of knowledge discovery from web logs. The data source in the form of web access logs allows, after appropriate preprocessing, the use of a number of techniques that are designed to deal with knowledge discovery. By applying these techniques to preprocessed data, it is possible to classify user behavior into groups, to discover interesting associations in user behavior, or to discover previously unknown sequences in common user behavior.
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Use of Sequential Pattern Mining in Google Analytics
Viskievič, Gergő ; Šabatka, Pavel (referee) ; Luhan, Jan (advisor)
The bachelor thesis focuses on the design and development of an algorithm for sequential pattern mining in Google Analytics 4 data. Presents and analyzes available algorithms for sequential pattern mining. Analyzes the data model and the use of Google Analytics 4. Based on the requirements of business processes, the algorithm is proposed suitable for the expected input data.
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Application for Management and Analysis of Data About Games of Chess
Kunčar, Petr ; Šebek, Michal (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with design and implementation of system for management and analysis of data about games of chess. The games of chess are stored in a database, to which they are uploaded by means of the system. There is also the AprioriAll algorithm implemented to find sequential patterns occuring in the data. Except of mining sequential patterns, the functionality of tree creation and searching in the data is also implemented. The data about games of chess are stored in a form of standard PGN files.
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Methods for Mining Sequential Patterns
Fekete, Martin ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
Sequential pattern mining is a field of data mining with wide applications. Currently, there are a number of algorithms and approaches to the problem of sequential pattern mining. The aim of this work is to design and implement an application designed for sequential pattern mining and use it to experimentally compare the chosen algorithms. Experiments are performed with both synthetic and real databases. The output of the work is a summary of the advantages and disadvantages of each algorithm for different kinds of input databases and an application implementing the selected algorithms of the SPMF library.
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Knowledge Discovery from Web Logs
Valaštín, Samuel ; Rychlý, Marek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with the problem of knowledge discovery from web logs. The data source in the form of web access logs allows, after appropriate preprocessing, the use of a number of techniques that are designed to deal with knowledge discovery. By applying these techniques to preprocessed data, it is possible to classify user behavior into groups, to discover interesting associations in user behavior, or to discover previously unknown sequences in common user behavior.
|
|
|
Use of Sequential Pattern Mining in Google Analytics
Viskievič, Gergő ; Šabatka, Pavel (referee) ; Luhan, Jan (advisor)
The bachelor thesis focuses on the design and development of an algorithm for sequential pattern mining in Google Analytics 4 data. Presents and analyzes available algorithms for sequential pattern mining. Analyzes the data model and the use of Google Analytics 4. Based on the requirements of business processes, the algorithm is proposed suitable for the expected input data.
|
|
|
Methods for Mining Sequential Patterns
Fekete, Martin ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
Sequential pattern mining is a field of data mining with wide applications. Currently, there are a number of algorithms and approaches to the problem of sequential pattern mining. The aim of this work is to design and implement an application designed for sequential pattern mining and use it to experimentally compare the chosen algorithms. Experiments are performed with both synthetic and real databases. The output of the work is a summary of the advantages and disadvantages of each algorithm for different kinds of input databases and an application implementing the selected algorithms of the SPMF library.
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|
|
Application for Management and Analysis of Data About Games of Chess
Kunčar, Petr ; Šebek, Michal (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with design and implementation of system for management and analysis of data about games of chess. The games of chess are stored in a database, to which they are uploaded by means of the system. There is also the AprioriAll algorithm implemented to find sequential patterns occuring in the data. Except of mining sequential patterns, the functionality of tree creation and searching in the data is also implemented. The data about games of chess are stored in a form of standard PGN files.
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