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Web Page Segmentation Algorithms
Laščák, Tomáš ; Burgetová, Ivana (referee) ; Burget, Radek (advisor)
Segmentation of web pages is one of the disciplines of information extraction. It allows to divide the page into different semantic blocks. This thesis deals with the segmentation as such and also with the implementation of the segmentation method. In this paper, we describe various examples of methods such as VIPS, DOM PS etc. There is a theoretical description of the chosen method and also the FITLayout Framework, which will be extended by this method. The implementation of the chosen method is also described in detail. The implementation description is focused on describing the different problems we had to solve. We also describe the testing that helped to reveal some weaknesses. The conclusion is a summary of the results and possible ideas for extending this work.
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Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
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Application of Unsupervised Learning Methods in Graph Similarity Search
Sabo, Jozef ; Burgetová, Ivana (referee) ; Křivka, Zbyněk (advisor)
Goal of this master's thesis was in cooperation with the company Avast to design a system, which can extract knowledge from a database of graphs. Graphs, used for data mining, describe behaviour of computer systems and they are anonymously inserted into the company's database from systems of the company's products users. Each graph in the database can be assigned with one of two labels: clean or malware (malicious) graph. The task of the proposed self-learning system is to find clusters of graphs in the graph database, in which the classes of graphs do not mix. Graph clusters with only one class of graphs can be interpreted as different types of clean or malware graphs and they are a useful source of further analysis on the graphs. To evaluate the quality of the clusters, a custom metric, named as monochromaticity, was designed. The metric evaluates the quality of the clusters based on how much clean and malware graphs are mixed in the clusters. The best results of the metric were obtained when vector representations of graphs were created by a deep learning model (variational graph autoencoder with two relation graph convolution operators) and the parameterless method MeanShift was used for clustering over vectors.
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Web Server for Protein Secondary Structure Prediction
Villem, Lukáš ; Očenášek, Pavel (referee) ; Burgetová, Ivana (advisor)
This master’s thesis deals with protein secondary structure prediction. There is a theoretical introduction followed by study of available tools, proposal and implementation of web application, which combines functionality of several web tools used to predict secondary structure. User is asked to choose prediction methods and insert input sequence as plain text or upload a file. Results collected from selected tools serve to convert data into common format, show the result and create new type of prediction. Finally, the testing is applied and influences of tools are adjusted in order to increase percentage of prediction. The output of application is a result of prediction also available as plain text or as a file.
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DNA Sequence Compression
Friedrich, Tomáš ; Burgetová, Ivana (referee) ; Martínek, Tomáš (advisor)
The increasing volume of biological data requires finding new ways to save these data in genetic banks. The target of this work is design and implementation of a novel algorithm for compression of DNA sequences. The algorithm is based on aligning DNA sequences agains a reference sequence and storing only diferencies between sequence and reference model. The work contains basic prerequisities from molecular biology which are needed for understanding of algorithm details. Next aligment algorithms and common compress schemes suitable for storing of diferencies agains reference sequence are described. The work continues with a description of implementation, which is follewed by derivation of time and space complexity and comparison with common compression algorithms. Further continuation of this thesis is discussed in conclusion.
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Recursive Web Search in KDE
Hefka, Lukáš ; Burgetová, Ivana (referee) ; Burget, Radek (advisor)
The bachelor thesis deals with problems related to web sites browsing from the KDE desktop environment. Part of this thesis is to introduce the application interface of this environment, suggestion description and application amplementation. The thesis supports range of restrictions both for searching area and searching itself. Application goes through the internet with the help of recursion and hypertext links. In conclusion there are descriobed application advatages in comparison with other alternative.
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Cluster Analysis Module of a Data Mining System
Hlosta, Martin ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with the design and implementation of a cluster analysis module for currently developing datamining system DataMiner on FIT BUT. So far, the system lacked cluster analysis module. The main objective of the thesis was therefore to extend the system of such a module. Together with me, Pavel Riedl worked on the module. We have created a common part for all the algorithms so that the system can be easily extended to other clustering algorithms. In the second part, I extended the clustering module by adding three density based clustering aglorithms - DBSCAN, OPTICS and DENCLUE. Algorithms have been implemented and appropriate sample data was chosen to verify theirs functionality.
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Project of New Computer Laboratory Stablishment
Hošták, Martin ; Burgetová, Ivana (referee) ; Květoňová, Šárka (advisor)
The main objective of this thesis is planning of new computer laboratory stablishment with the aid of project management philosophy. The main attention is paid to using Microsoft Project 2003 aplication. Results of consultation with the head of similarly conducted project, which was successfully implemented, was used as a solution to the project. Firstly, a structure of the work team is built-up. Secondly, a work break down structure, consequently structure among activities. Finally, everything is optimized and scheduled. Application Microsoft Project 2003 was used as software support, which was the main factor that helps to describe and schedule the project. The main aim of my thesis is text production of a new project to build a new computer laboratory.
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Mobile Application Identification Based on TLS Data
Borbély, Richard ; Matoušek, Petr (referee) ; Burgetová, Ivana (advisor)
This thesis deals with identification of mobile applications based on data from network protocol TLS. It conducts a research of values from the TLS handshake, specifically of JA3, JA3S and SNI values. The work represents an application that includes an algorithm performing a classification over TLS data. The results of the classification represent information based on which we can decide, if the identification of the apps was successful. This method allowed to identify 17 of the 18 given applications. The benefit of this work is the ability to identify mobile apps based on JA3, JA3S and SNI values and for example, it can be used in network administration.
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