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Automatic Generation of Synthetic XML Documents
Betík, Roman ; Holubová, Irena (advisor) ; Svoboda, Martin (referee)
The aim of this thesis is to research the current possibilities and limitations of automatic generation of synthetic XML and JSON documents used in the area of Big Data. The first part of the work discusses the properties of the most used XML data generators, Big Data and JSON generators and compares them. The next part of the thesis proposes an algorithm for data generation of semistructured data. The main focus of the algorithm is on the parallel execution of the generation process while preserving the ability to control the contents of the generated documents. The data generator can also use samples of real data in the generation of the synthetic data and is also capable of automatic creation of simple references between JSON documents. The last part of the thesis provides the results of experiments with the data generator exploited for the purpose of testing database MongoDB, describes its added value and compares it to other solutions. Powered by TCPDF (www.tcpdf.org)
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Data journalism aimed by Datablog IHNED.cz
Hrbková, Nikola ; Láb, Filip (advisor) ; Kasík, Pavel (referee)
Now when information is abundant, practice of Data Journalism is quickly becoming a core technique of the 21st century newsrooms. The diploma thesis "Data Journalism aimed by Datablog IHNED.cz" is focused on introducing Data Journalism as a genre responding to the changes in the society and the technology development. The theoretical part concerns with the history of the subject, the workflow of Data Journalism in the newsrooms and the limitations; such as inappropriate business models, difficult process of collecting data or the lack of training. The main goal of the research is to map the work of the Czech data team in the IHNED.cz and compare the results with the work of teams in Australia. The research methods are combination of quantitative and qualitative analyses. The main source of information are interviews conducted with data journalists from the Czech Republic and Australia. On top of that the research gives deeper understanding of how the integration of data journalists in the newsrooms affect the way journalism can support the existence of media organizations and contribute to the public good. The last part offers predictions of the future of Data Journalism.
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New challenges of the surveillance theory
Lacinová, Miroslava ; Štogrová Jedličková, Petra (advisor) ; Malečková, Dita (referee)
The main aim of this diploma thesis, that names "New challenges of the Surveillance theory", is to describe the surveillance theory in today's social network society by using information theory. Accordingly, I will verify the theory of surveillance in two case studies. First case study verifies an impact of Facebook's profiles content on the hiring decisions. The second case sudy analyzes regular day of concrete person in context of surveillance. Both case studies demonstrate surveillance in different surveillance sites.
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High Performance Analytics
Kalický, Andrej ; Kyjonka, Vladimír (advisor) ; Holubová, Irena (referee)
This thesis explains Big Data Phenomenon, which is characterised by rapid growth of volume, variety and velocity of data - information assets, and thrives the paradigm shift in analytical data processing. Thesis aims to provide summary and overview with complete and consistent image about the area of High Performance Analytics (HPA), including problems and challenges on the pioneering state-of-art of advanced analytics. Overview of HPA introduces classification, characteristics and advantages of specific HPA method utilising the various combination of system resources. In the practical part of the thesis the experimental assignment focuses on analytical processing of large dataset using analytical platform from SAS Institute. The experiment demonstrates the convenience and benefits of In-Memory Analytics (specific HPA method) by evaluating the performance of different analytical scenarios and operations. Powered by TCPDF (www.tcpdf.org)
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Platform for Defining and Processing of Data
Hala, Karel ; Večeřa, Martin (referee) ; Kříž, Jiří (advisor)
This diploma thesis deals with creating platform which serves for easy manipulation with large data set. There are numerous technical knowledge described in this thesis to understand web development. Later there are proposed approaches of how to make as easy as possible for user to define and work with large data sets. Platform is written and created in a way, that it is easy to extend eny part of it.
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Possibilities of Big Data use for Competitive Intelligence
Verníček, Marek ; Molnár, Zdeněk (advisor) ; Šperková, Lucie (referee)
The main purpose of this thesis is to investigate the use of Big Data for the methods and procedures of Competitive Intelligence. Among the goals of the work is a toolkit for small and large businesses which is supposed to support their work with the whole process of Big Data work. Another goal is to design an effective solution of processing Big Data to gain a competitive advantage in business. The theoretical part of the work processes available scientific literature in the Czech Republic and abroad as well as describes the current state of Competitive Intelligence, and Big Data as one of its possible sources. Subsequently, the work deals with the characteristics of Big Data, the differences from working with common data, the need for a thorough preparation and Big Data applicability for the methods of Competitive Intelligence. The practical part is focused on analysis of Big Data tools available in the market with regard to the whole process from data collection to the analysis report preparation and integration of the entire solution into an automated state. The outcome of this part is the Big Data software toolkit for small and large businesses based on their budget. The final part of the work is devoted to the classification of the most promising business areas, which can benefit from the use of Big Data the most in order to gain competitive advantages and proposes the most effective solution of working with Big Data. Among other benefits of this work are expansion of the range of resources for Competitive Intelligence and in-depth analysis of possibilities of Big Data usage, designed to help professionals make use of this hitherto untapped potential to improve market position, gain new customers and strengthen the existing user base.
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The Grid
Gajdošík, Andreas ; Magid, Václav (referee) ; Krekovič, Slavomír (advisor)
Work aims at consequences of fully developed infrastructure of web 2.0 and its wide social acceptance, which with cheap computing power leads to massive data interpretation. In relation to that this work uses public Facebook's data about user activity at right wing oriented Facebook pages which gathers and statisticaly analyzes. Result is then showed at web page which is designed to look close to the look of extreme right wing webs. Positive first sight impression of right wing sympathizers is then eroded with not so good empirical statistics. Under 100 users are commenting quite often so this right wing craziness looks like a small movement in the end. Therefore Grid stands somewhere between amateur sociol research and artistic intervention into public media space.
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The algorithm for the detection of positive and negative text
Musil, David ; Harár, Pavol (referee) ; Povoda, Lukáš (advisor)
As information and communication technology develops swiftly, amount of information produced by various sources grows as well. Sorting and obtaining knowledge from this data requires significant effort which is not ensured easily by a human, meaning machine processing is taking place. Acquiring emotion from text data is an interesting area of research and it’s going through considerable expansion while being used widely. Purpose of this thesis is to create a system for positive and negative emotion detection from text along with evaluation of its performance. System was created with Java programming language and it allows training with use of large amount of data (known as Big Data), exploiting Spark library. Thesis describes structure and handling text from database used as source of input data. Classificator model was created with use of Support Vector Machines and optimized by the n-grams method.
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Temporary Zone
Maňas, Kristian ; Zálešák, Jan (referee) ; Kögler, Žaneta (advisor)
Temporary zone is open-source design studio. This diploma thesis is concerned with origin of the project and its theoretic background. Theoretic part of the thesis defines the term „open-source design“ and tries to explain motivations behind creation of Temporary zone.
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