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Analysis of Mobile Devices Network Communication Data
Abraham, Lukáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
At the beginning, the work describes DNS and SSL/TLS protocols, it mainly deals with communication between devices using these protocols. Then we'll talk about data preprocessing and data cleaning. Furthermore, the thesis deals with basic data mining techniques such as data classification, association rules, information retrieval, regression analysis and cluster analysis. The next chapter we can read something about how to identify mobile devices on the network. We will evaluate data sets that contain collected data from communication between the above mentioned protocols, which will be used in the practical part. After that, we finally get to the design of a system for analyzing network communication data. We will describe the libraries, which we used and the entire system implementation. We will perform a large number of experiments, which we will finally evaluate.
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Information Retrieval in Research Portals
Ďulík, Jan ; Smrž, Pavel (referee) ; Schmidt, Marek (advisor)
This paper deals with the information retrieval in research portals with the intention of the retrieval in scientific publications. We define concepts related to the information retrieval, classification and knowledge representation. We also present existing search tools used as the initial inspiration for the design of the search intergace. Futhermore we describe the implementation as well as the process of collecting sample data. In the last chapter we discuss usability of the developed web application.
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Automatically Updated Bibliography
Valo, Boris ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
This paper describes the development of application for automatically updated bibliography. Nowadays, many Internet users search informations they need, this is important especially in sets of scientific publications and articles. The aim of this thesis is convenient tool for users to create their own portal. This is achieved by storing documents and their subsequent search using ElasticSearch. Retrieval is made by Boolean queries and additional search using similarity search tool MoreLikeThis. At the end of this thesis is described the way of testing and evaluation of retrieval.
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Video Retrieval
Černý, Petr ; Mlích, Jozef (referee) ; Chmelař, Petr (advisor)
This thesis summarizes the information retrieval theory, the relational model basic and focuses on the data indexing in relational database systems. The thesis focuses on multimedia data searching. It includes description of automatic multimedia data content extraction and multimedia data indexing. Practical part discusses design and solution implementation for improving query effectivity for multidimensional vector similarity which describes multimedia data. Thesis final part discusses experiments with this solution.
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Information Retrieval
Šabatka, Pavel ; Bartík, Vladimír (referee) ; Chmelař, Petr (advisor)
The purpose of this thesis is a summary of theoretical knowledge in the field of information retrieval. This document contains mathematical models that can be used for information retrieval algorithms, including how to rank them. There are also examined the specifics of image and text data. The practical part is then an implementation of the algorithm in video shots of the TRECVid 2009 dataset based on high-level features. The uniqueness of this algorithm is to use internet search engines to obtain terms similarity. The work contains a detailed description of the implemented algorithm including the process of tuning and conclusions of its testing.
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High-performance exploration and querying of selected multi-dimensional spaces in life sciences
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Glaab, Enrico (referee) ; Svozil, Daniel (referee)
This thesis studies, implements and experiments with specific application-oriented approaches for exploring and querying multi-dimensional datasets. The first part of the thesis scrutinizes indexing of the complex space of chemical compounds, and details a design of high-performance retrieval system for small molecules. The resulting system is then utilized within a wider context of federated search in heterogeneous data and metadata related to the chemical datasets. In the second part, the thesis focuses on fast visualization and exploration of many-dimensional data that originate from single- cell cytometry. Self-organizing maps are used to derive fast methods for analysis of the datasets, and used as a base for a novel data visualization algorithm. Finally, a similar approach is utilized for highly interactive exploration of multimedia datasets. The main contributions of the thesis comprise the advancement in optimization and methods for querying the chemical data implemented in the Sachem database cartridge, the federated, SPARQL-based interface to Sachem that provides the heterogeneous search support, dimensionality reduction algorithm EmbedSOM, design and implementation of the specific EmbedSOM-backed analysis tool for flow and mass cytometry, and design and implementation of the multimedia...
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The interaction of information science and cognitive sciences with emphasis on information retrieval
Pilecká, Věra ; Papík, Richard (advisor) ; Sedláčková, Beáta (referee) ; Rankov, Pavel (referee)
Mgr. Věra Pilecká The interaction of information science and cognitive sciences with emphasis on information retrieval (dissertation thesis) (Vzájemné ovlivňování informační vědy a kognitivních věd s důrazem na vyhledávání informací) Abstract Focus of this thesis is on the description of the interaction of information science and cognitive sciences with emphasis on information retrieval which is influenced by some of the cognitive aspects. The introductory chapter deals with the definition of information science and paradigms inspired by a cognitive approach (cognitive and socio-cognitive paradigm). Then a cognitive science is defined including its basis, methods and application. In the third chapter, a comparison between information and cognitive science is included, and their interaction and common interests are described. Fourth chapter focuses on information retrieval and influencing factors, including search methods, user information behaviour, and user cognitive characteristics and mental models. The final chapter presents two surveys focused on the use of intuitive and analytical information retrieval styles during searching on Google, and the perception of the differences between traditional and online teaching of the effective reading techniques. Both surveys illustrate the influence of users'...
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System for Agregation of Information from Public Databases
Pojsl, Jakub ; Rychlý, Marek (referee) ; Očenášek, Pavel (advisor)
The thesis focuses on the design and implementation of a system for law firms, designed to automatically retrieve relevant information from public databases. Initially, the reader is familiarized with the significance and accessibility of chosen public registers within the context of prevailing legislation. This is followed by an analysis of the processes within law firms and the existing information systems in their area. Subsequently, the focus shifts to the detailed specification and design of this system, encapsulating functionalities for client management, document organization, mail handling, and simplified billing procedures. The practical aspect of the thesis includes the actual implementation of the system, with a particular focus on user interface design, data accessibility from external sources, and the streamlining of law firm processes. The outcome of this work is a comprehensive system to aid the law firm’s operations. This includes aggregating data from selected public databases, monitoring changes in court and insolvency proceedings, and integrating with a government electronic mailbox system. Additionally, the system offers a publicly available interface for obtaining aggregated data from public registers. The system has been deployed in a testing environment, paving the way for further enhancements and demonstrating the potential for real-world application.
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Designing a Multilingual Fact-Checking Dataset from Existing Question-Answering Data
Kamenický, Daniel ; Aparovich, Maksim (referee) ; Fajčík, Martin (advisor)
Tato práce se zabývá nedostatkem vícejazyčných datových sad pro kontrolu faktů, které by obsahovaly důkazy podporující nebo vyvracející fakt. Proto se tato práce zabývá převodem datového souboru pro kontrolu faktů z již existujícího datového souboru otázek a odpovědí. V této práci jsou studovány dva přístupy ke konverzi datové sady. Prvním přístupem je vytvoření datové sady založené na jednojazyčném předem natrénovaném seq-2-seq modelu T5. Model je trénován na anglickém datovém souboru. Vstupy a výstupy jsou překládány do požadovaných jazyků. Druhým přístupem je využití vícejazyčného modelu mT5, který přebírá vstup a generuje výstup v požadovaném jazyce. Pro vícejazyčný model je zapotřebí přeložit trénovací datové sady. Jako hlavní problém této práce se ukázal překlad, který v málo zdrojovém jazyce dosáhl kolem 30 % úspěšnosti. Experimenty ukázaly lepší výsledky v tvrzeních generovaných z jednojazyčného modelu s využitím strojového překladu. Na druhou stranu, tvrzení generované z vícejazyčného modelu dosáhly úspěšnosti 73 % oproti tvrzením z jednojazyčného modelu s dosaženou úspěšností 88 %. Modely byly vyhodnoceny modelem ověřování faktů založeném na TF-IDF. Dosažená přesnost modelu na obou datových sadách se blíží 0,5. Z toho lze usoudit, že výsledné datové sady mohou být náročné pro modely ověřování faktů.
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Matching Images to Texts
Hajič, Jan ; Pecina, Pavel (advisor) ; Průša, Daniel (referee)
We build a joint multimodal model of text and images for automatically assigning illustrative images to journalistic articles. We approach the task as an unsupervised representation learning problem of finding a common representation that abstracts from individual modalities, inspired by multimodal Deep Boltzmann Machine of Srivastava and Salakhutdinov. We use state-of-the-art image content classification features obtained from the Convolutional Neural Network of Krizhevsky et al. as input "images" and entire documents instead of keywords as input texts. A deep learning and experiment management library Safire has been developed. We have not been able to create a successful retrieval system because of difficulties with training neural networks on the very sparse word observation. However, we have gained substantial understanding of the nature of these difficulties and thus are confident that we will be able to improve in future work.
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