Thesis Details

Metody dolování sekvenčních vzorů

Bachelor's Thesis Student: Fekete Martin Academic Year: 2020/2021 Supervisor: Bartík Vladimír, Ing., Ph.D.
Language
Slovak
Abstract

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.

Keywords

knowledge discovery from databases, data mining, sequential patterns, sequential pattern mining, apriori, pattern growth, early candidate pruning, GSP, SPADE, SPAM, CM-SPADE, CM-SPAM, LAPIN, PrefixSpan, SPMF

Department
Department of Information Systems FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
18 June 2021
Reviewer
Burgetová Ivana, Ing., Ph.D.
Committee
Kolář Dušan, doc. Dr. Ing. (DIFS FIT BUT), předseda
Burgetová Ivana, Ing., Ph.D. (DIFS FIT BUT), člen
Fučík Otto, doc. Dr. Ing. (DCSY FIT BUT), člen
Hrubý Martin, Ing., Ph.D. (DITS FIT BUT), člen
Španěl Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Citation
FEKETE, Martin. Metody dolování sekvenčních vzorů. Brno, 2021. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2021-06-18. Supervised by Bartík Vladimír. Available from: https://www.fit.vut.cz/study/thesis/23975/
BibTeX 
@bachelorsthesis{FITBT23975,
    author = "Martin Fekete",
    type = "Bachelor's thesis",
    title = "Metody dolov\'{a}n\'{i} sekven\v{c}n\'{i}ch vzor\r{u}",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2021,
    location = "Brno, CZ",
    language = "slovak",
    url = "https://www.fit.vut.cz/study/thesis/23975/"
}

Theses

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