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Knowledge Discovery from Web Logs
Valaštín, Samuel ; Rychlý, Marek (oponent) ; Bartík, Vladimír (vedoucí práce)
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 (oponent) ; Luhan, Jan (vedoucí práce)
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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Aplikace pro správu a analýzu dat o šachových partiích
Kunčar, Petr ; Šebek, Michal (oponent) ; Bartík, Vladimír (vedoucí práce)
Tato bakalářská práce se zabývá návrhem a implementací systému pro správu a analýzu dat ze šachových partií. Partie jsou uchovávány v úložišti dat, do kterého jsou nahrány pomocí vytvořeného systému. Byl implementován také algoritmus AprioriAll, který je použit k nalezení sekvenčních vzorů v uložených datech. Kromě toho jsou také implementovány funkce vytvoření stromu a vyhledávání v datech. Data o šachových partiích jsou uloženy ve standardním formátu PGN.
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Methods for Mining Sequential Patterns
Fekete, Martin ; Burgetová, Ivana (oponent) ; Bartík, Vladimír (vedoucí práce)
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 (oponent) ; Bartík, Vladimír (vedoucí práce)
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 (oponent) ; Luhan, Jan (vedoucí práce)
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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Methods for Mining Sequential Patterns
Fekete, Martin ; Burgetová, Ivana (oponent) ; Bartík, Vladimír (vedoucí práce)
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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Aplikace pro správu a analýzu dat o šachových partiích
Kunčar, Petr ; Šebek, Michal (oponent) ; Bartík, Vladimír (vedoucí práce)
Tato bakalářská práce se zabývá návrhem a implementací systému pro správu a analýzu dat ze šachových partií. Partie jsou uchovávány v úložišti dat, do kterého jsou nahrány pomocí vytvořeného systému. Byl implementován také algoritmus AprioriAll, který je použit k nalezení sekvenčních vzorů v uložených datech. Kromě toho jsou také implementovány funkce vytvoření stromu a vyhledávání v datech. Data o šachových partiích jsou uloženy ve standardním formátu PGN.
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