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Intelligent Data Scraping in a Web Browser
Maštera, František ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
The goal of this thesis is to extract data from web pages without the knowledge of their internal structure. The point is to recognize the structure using an algorithm and a given input information about the content that the user wants to extract. The structure analysis is then followed by the content extraction itself. An average success rate of over 80% was achieved on selected sets of websites. The resulting algorithm represents a new approach to data extraction and can be deployed in the real world or can be a part of further development.
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Portal for Aggregation of Data from Web Sources
Mikita, Tibor ; Křivka, Zbyněk (referee) ; Burget, Radek (advisor)
This thesis deals with data extraction and data aggregation from heterogeneous web sources. The goal is to create a platform and a functional web application using appropriate technologies. The main focus of the thesis is on the application design and implementation. The application domain is accommodation or lease of apartments. For the data extraction, we use the portal API or a wrapper. Obtained data is stored in a document database. In this thesis, we managed to design and implement a system that allows to obtain rental ads from multiple web sources at the same time and to present them in a uniform way.
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Environment for analyzing suspicious device
Procházka, Jan ; Martinásek, Zdeněk (referee) ; Malina, Lukáš (advisor)
This bachelor thesis focuses on a design of enviroment for analysis of a suspicious device. Such device may be for example a disc contaminated by malicious code or a mobile device. The aim of this work is to design an efficient and simple solution using open source products. The final designed environment should be capable of performing both surface and in-depth data analysis. The theoretical part offers an information related to the scope of addressed problem and includes terms such as Sandbox, Malware, Android. These are described from the point of view of understanding the analysis of malware occurring predominantly on mobile devices. The practical part describes the used hardware and software for the design of the environment and it contains examples of analyzes of the external devices contaminated by a malcode. These examples are mainly for Android mobile devices.
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Relationship between Changes in Betting Odds and Results of Football Matches
Jurkovič, Juraj ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The goal of this thesis is to demonstrate techniques for solving web scraping and knowledge discovery tasks. The case study is focused on the extraction of data from bookmaker websites and subsequent analysis of collected data. The thesis demonstrates the implementation of web scraping task in Python language. The thesis describes selected implementation details for developing such a system and proposes a database schema that can be used for this purpose. Collected data is analyzed using statistical methods and frequent patterns are discovered in odds movements using apriori algorithm. Discovered relationships and frequent patterns are presented to the end user.
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Analýza spolehlivosti forenzních nástrojů pro zkoumání malé digitální techniky
PĚSTOVÁ, Karolína
This bachelor thesis deals with forensic tools for investigating small digital devices. In theoretical part are described principles in digital forensic analysis and approaches for examining mobile phones. In practical part are analysed selected mobile phones with tools for investigating small digital devices. In this part are evaluated results and proposed a solution for acquiring the most relevant data.
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Sentiment Analysis in Automotive Industry
Bezák, Adam ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
The main theme of this thesis is to familiarize with the basic methods of sentiment analysis on social networks. Thesis’s theme is aimed on the automotive industry, although this prinicipal can be used in any different examined branch. The basis of the practical part is to obtain data from the social networks, analyze them and then index them into ElasticSearch database. Another goal of the thesis is to visualize these data by means of a web portal. Created web portal provides various statistics of the leading automobile brands, an overview of new trends or the aspect visualization of the individual cars.
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Design and Implementation of System for Aggregations of Real Estate Offers in the Czech Republic
Drobník, Jakub ; Kučera, Jan (advisor) ; Chlapek, Dušan (referee)
The diploma thesis deals with the design and implementation of software for aggregations of real estate offers in the Czech Republic. The aim of the thesis is to create a system which aggregates the data of real estate offers from web pages. This thesis consists of two basic parts. The context of creating the system is described in the first part. The author discusses ways to retrieve data from websites - especially the extraction of data using automated robots - in the first part of the thesis. The design and implementation of the system are described in the second part. The author and sponsor define requirements for the system in the second part of the thesis. The outcome of this thesis is a prototype that aggregates data from real estate portals into the prepared database. The main contribution of the thesis is an example of a possible approach that can aggregate data from a particular market segment and put it into the database.
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Web page data figure finder
Janata, Dominik ; Vojtáš, Peter (advisor) ; Nečaský, Martin (referee)
The thesis treats automatic extraction of semantic data from Web pages. Within this broad problem, it focuses on finding values of data figures within the page presenting certain entity (e.g. price of a laptop). The main idea we wanted to evaluate is that a figure can be found using its context in the page: the words that surround it and values of the attributes of the containing HTML tags, class attribute in particular. Our research revealed there are two types of contemporary solutions of this problem: either the author of the Web page must inline semantic information inside the markup of the page or there are commercial tools that can be trained to parse a particular page format (targetting pages from a single Web domain). We examined the possibilities of developing a general solution that would - for given entity - find its properties across the Web domains using text analysis and machine learning. The naïve algorithm had about 30% accuracy, the lear- ning algorithms had the accuracy between 40 and 50% in finding the properties. Despite the accuracy is not acceptable for a final solution, we believe it confirms the potential of the idea. Keywords: Web pages data extraction 1
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Extracting Linked Data from Excel Files
Dembinný, Šimon ; Nečaský, Martin (advisor) ; Bednárek, David (referee)
Title: Extracting Linked Data from Excel files Author: Šimon Dembinný Department: Department of Software Engineering Supervisor of the bachelor thesis: Mgr.Martin Nečaský, Ph.D, Department of Software Engineering at Faculty of Mathematics and Physics of Charles University Abstract: The major part of the thesis rests in the development of an application for extracting Linked Data from Excel files. The application is created as Microsoft Excel Add-on. The comparison with best freely available tool for Linked Data extraction from table data "Open refine" is provided in the theoretical part together with explanation of the concept of Linked Data itself.
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Image object detection using template
Novák, Pavel ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This Thesis is focused to Image Object Detection using Template. Main Benefit of this Work is a new Method for sympthoms extraction from Histogram of Oriented Gradients using set of Comparators. In this used Work Methods of Image comparing and Sympthoms extraction are described. Main Part is given to Histogram of Oriented Gradients Method. We came out from this Method. In this Work is used small training Data Set (100 pcs.) verified by X-Validation, followed by tests on real Sceneries. Achieved success Rate using X-Validation is 98%. for SVM Algorithm.
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