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Text Classification Methods in the Context of Web Pages
Trstenský, Patrik ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
This work deals with the issue of text classification in the context of websites. It examines available classification methods and their accuracy over web page plain text. It deals with constructing a dataset for training these methods for a specific domain. We obtain data for creating the dataset from publicly available websites that utilize RDF documents defined in HTML code. The conclusion of the work consists of the creation of two datasets for two different domains. Furthermore, the use of these datasets for training models and testing of their accuracy.
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Porting of Plaso Extractors to the Apache Spark Platform
Baláž, Miroslav ; Burget, Radek (referee) ; Rychlý, Marek (advisor)
The theoretical part discusses the functioning and architecture of the Plaso tool. The thesis further explores current tools that implement distributed computational models. It describes their architecture, data abstracts and how they work. The thesis also describes current tools that implement distributed storage. The work includes the creation of the Plasospark tool, which converts the computation of the Plaso tool to the Spark platform and uses the Hadoop HDFS storage for forensic data.
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Optimisation of Testing Environment Allocation in Testing Farm Service
Šimko, Daniel ; Burget, Radek (referee) ; Rychlý, Marek (advisor)
Cieľom tejto práce je implementácia `poličky' a poprednej prípravy virtuálnych strojov ako optimalizácií v procese zaisťovania virtuálnych strojov pri testovaní softvéru. Táto práca popisuje proces získavania virtuálnych strojov službou Artemis v prostredí služby Testing Farm a zmeny vykonané v mechanizmoch zabezpečujúcich získavanie virtuálnych strojov tak, aby bol znížený čas medzi vytvorením požiadavku a poskytnutím plne funkčného stroja.
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Web Application for Managing Software Detection Rules in Software Asset Management
Drtil, David ; Burget, Radek (referee) ; Rychlý, Marek (advisor)
The content of this thesis is the management of a library of rules used for software recognition on devices. The application has special purpose in the Software Asset Management system and other components depend on it. Software product recognition is performed by applying rules to the information present about the installation of the programs. Formats for writing rules and methodology may be different, but they are based on the original Alvao best practice. The work is primarily focused on simplifying and automating the process of creating or adjusting rules by means of appropriate suggesting of the resulting rules, categorization or other related actions.
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Authentication Framework for Web Applications
Michalica, David ; Rychlý, Marek (referee) ; Burget, Radek (advisor)
The subject of this work is to create a microservice for user authentication and user account management. The server side implementation is in C# and .NET framework. The user interface is implemented in Javascript using the React library. MySQL database is used for the data layer of the application, but the modular design of the application allows to use any type of database after minor modifications. JWT tokens are used for authentication. The application allows the client to log in using third party accounts, such as an existing Google account.
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System for Acquisition and Analysis of Real Estate Data from WWW
Karpíšek, Miroslav ; Hynek, Jiří (referee) ; Burget, Radek (advisor)
This project is focused on designing a system for automatic extraction of real estate data from real estate servers. In the theoretical part, this work is first placed in the context of data engineering. Subsequently, the used technologies and system components that were used in the project are described, same as their importance within the framework of the created platform intended for real estate investors for the purpose of renting them. The work also includes an evaluation of the basic methods used to predict the rent amount, which is used to calculate the return of investment.
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Layout-based Data Extraction from Documents
Sedláček, Martin ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
This thesis deals with automated data extraction from medical reports in PDF format based on document layout analysis. The main content of the thesis is an introduction to data extraction, a comparison of existing tools and a presentation of the design and requirements of the developed tool, which will be based on the FitLayout application framework. The thesis then describes the actual implementation of the tool in Java and comments on the results achieved by the tool on real data.
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Data Analysis and Visualization of the Brno City Council
Zaklová, Kristýna ; Burget, Radek (referee) ; Hynek, Jiří (advisor)
The aim of this thesis was to analyze the data from the Brno City Council voting and propose their visualization, i.e. an understandable presentation of the obtained information and statistics about the representatives' decisions. The system was designed to be applicable to other councils, and thus, it includes an input model for voting data. The developed solution is a web application with a client-server architecture, and it was implemented using the Flask framework and the React library. The correctness of the created dataset was verified against the minutes of council meetings. The application itself was tested with a selected sample of users and in real operation. The main benefits of this work include providing more transparent information about the activities of Brno city councillors, creating an analytical tool for Brno citizens, and offering the potential to extend the solution to other municipalities.
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Machine Learning Methods for Web Documents
Katrňák, Josef ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
This work aims to use machine learning techniques for the classification of specific parts of web page content. First, current methods for representing and classifying web page content using machine learning methods are described. For web page representation, the thesis focuses on the experimental tool FitLayout, whose visual representation of web pages serves as input for further processing and subsequent training of machine learning models. The work results in trained models that classify specific parts of the web page content. The model architecture is based on graph neural networks. For the experiments, a dataset of publicly available websites containing pages of products sold online is used. The advantage of the proposed and implemented approach is information extraction independent of the structure and language of a web page.
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Vision-based Web Page Segmentation
Maštera, František ; Hynek, Jiří (referee) ; Burget, Radek (advisor)
The FitLayout library offers a suite of implemented web page segmentation algorithms along with a number of tools for their evaluation and further development. The goal of this thesis is to extend this suite by another of already existing algorithms. To meet this goal, the Cormier et al. algorithm was chosen and integrated into the FitLayout. The plausibility of its implementation against its publication has been duly verified. Its extensive evaluation was also carried out to determine its properties and behaviour under different circumstances, which revealed algorithm settings that improve the quality of its outputs on the tested data sample by up to 9.89 %. As a result of this thesis, the FitLayout library has been extended with a new web page segmentation algorithm, which can be used in further research in this area that can be supported with the results found in this thesis.
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