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Processing Czech in Python
Novotný, Zdeněk ; Schmidt, Marek (referee) ; Smrž, Pavel (advisor)
This bachorelor´s thesis presents some ways of Czech language processing. The first part contains a general destription of NLTK system. Some of aftermentioned functions were inspired by NLTK functions. There are described functions which attend to inflection and inflexion of various words class in Czech language. Next part is focused on processing of the text in Czech language in which are found and marked each sentences and other parts. Last part describes possibillity of tranformations rules application for each part of text. Results after rules application could be represented graphically.
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Internet Robot for an Assistance of Calendar Scheduling
Klos, Jakub ; Očenášek, Pavel (referee) ; Smrčka, Aleš (advisor)
This bachelor thesis deals with the development of the internet robot for assistance of calendar scheduling. The robot and a user comunicate with a subset of English. User does not have to study special syntax of the orders which makes using of the robot-calendar much simplier. This easement is the main contribution of the work. This kind of control should help especially to the users with lesser amount of computer skills, for whom the special syntax-oriented-control might be difficult. The XMPP protocol is used for a comunication which is of instant messaging type. NLTK toolkit was used for natural language processing. The source code of the robot is completely programmed in Python programming language. The work also deals with possibilities of robot's further development.
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Temporal Logics for a Man
Žilka, Lukáš ; Letko, Zdeněk (referee) ; Smrčka, Aleš (advisor)
The work deals with the automated translation of a natural language to temporal logic. Existing research attempts are summarized and built upon. For specificating the temporal properties a subset of English is introduced. The main contribution of the work is the proposed algorithm of translation of a property in the given language to LTL temporal logic, based on processing of and finding patterns in grammatical dependencies of The Stanford English Parser. Future research directions are discussed at the end.
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Consistency Checking of Relations Extracted from Text
Stejskal, Jakub ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This bachelor thesis is dedicated to mechanical techniques that are used in the natural language processing and information extraction from particular text. It is approaching the general methods that starting to process the raw text and it continues to the relations extraction from processed language constructs, moreover it provides options for the use of obtained relational data which can be seen for example in the project DBpedia. Another milestone of the described bachelor thesis is the design and implementation of an automated system for extracting information about entities, which do not have their own article on the English version of Wikipedia. Thesis also presents algorithms developed for the extraction of entities with their own name, the verification of the articles ‘existence of the extracted entities and finally the actual extraction of information about individual entities, which can be used during the information consistency checking. In the end, it can be seen the results and suggestions for further development of the created system.
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Mendel University performance analysis through data mining
Panggam, Osunam
This thesis explores the Mendel University performance analysis and the connection between the University ranking with the news articles and reviews. The study aims to analyze media coverage and review data on the universities over the years and their impact on the university's reputation and ranking. The research methodology involves web scraping news articles and reviews related to Mendel University and using data mining and NLP techniques to analyze their sentiment and topic distribution. Further, the qualitative data collected from news articles, online students’ reviews will be correlated with the University's ranking scores data over a past-years period to identify any patterns or relationships. The findings of the study will try to find insight into the impact of media coverage on university ranking and reputation. It will also shed light on the data mining techniques to analyze textual data related to the university for interesting patterns.
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Binární klasifikace zákaznických incidentů pomocí metod NLP
Pokorný, Jiří
This bachelor thesis focuses on building a model for binary classification of customer incidents within the SAP system. By classifying the individual sentences of incidents, the final category of the incident is predicted. The used text is in English. To compare traditional and modern approaches to text classification as well as obtain optimal results, a series of experiments is carried out using different methods of balancing the dataset, vector representation and classification. Finally, the results are analyzed and recommendation is formulated with regard to further development, including applying knowledge gained within the SAP environment.
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Generating Code from Textual Description of Functionality
Šamánek, Jan ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
S pokračujícím nástupem strojového učení a stále větších modelů neuronových sítí, roste i potřeba GPU akcelerovaných zdrojů a algoritmů pro podporu těchto modelů. Vzhledem k tomu, že velké jazykové modely jsou již dnes využívány jako asistenti při programování v moderních programovacích jazycích, mohli by s tímto problémem pomoci. Pokud se tyto modely dokáží naučit i méně známá paradigmata, jako je CUDA, mohly by pomoci s vývojem a udržování těchto systémů. Tato práce zkoumá schopnosti moderních jazykových modelů pro učení se CUDA jako programovacího paradigmatu a také vytvoření nové trenovací sady, určené pro tyto účely.
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Text Analysis in Specialized Translation: Accuracy and Error Rate
Parobková, Alžbeta ; Marcoň, Petr (referee) ; Dohnal, Přemysl (advisor)
Práca sa zameriava na prieskum a aplikáciu metód textovej analýzy, strojového prekladu na vyhodnotenie kvality technických textov, preložených práve pomocou strojového automatického prekladu. Praktická časť využíva tieto metódy na implementáciu algoritmu pre identifikáciu a klasifikáciu chýb. Ďaľšou časťou praktickej časti je aj aplikácia a natrénovanie neurónového modelu pre korekciu týchto chýb. Porovnanie chybovosti a presnosti prekladu rôznymi prekladačmi je potom preukázané nie len kvalitatívne, ale aj kvantitatívne pomocou štandartných metrík.
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Automatic detection and attribution of quotes
Ustinova, Evgeniya ; Hana, Jiří (advisor) ; Vidová Hladká, Barbora (referee)
Quotations extraction and attribution are important practical tasks for the media, but most of the presented solutions are monolingual. In this work, I present a complex machine learning-based system for extraction and attribution of direct and indirect quo- tations, which is trained on English and tested on Czech and Russian data. Czech and Russian test datasets were manually annotated as part of this study. This system is com- pared against a rule-based baseline model. Baseline model demonstrates better precision in extraction of quotation elements, but low recall. The machine learning-based model is better overall in extracting separate elements of quotations and full quotations as well. 1
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