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XML Databases for Dictionary Data Management
Samia, Michel ; Dytrych, Jaroslav (referee) ; Smrž, Pavel (advisor)
The following diploma thesis deals with dictionary data processing, especially those in XML based formats. At first, the reader is acquainted with linguistic and lexicographical terms used in this work. Then particular lexicographical data format types and specific formats are introduced. Their advantages and disadvantages are discussed as well. According to previously set criteria, the LMF format has been chosen for design and implementation of Python application, which focuses especially on intelligent merging of more dictionaries into one. After passing all unit tests, this application has been used for processing LMF dictionaries, located on the faculty server of the research group for natural language processing. Finally, the advantages and disadvantages of this application are discussed and ways of further usage and extension are suggested.
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Methods of Information Extraction
Adamček, Adam ; Smrž, Pavel (referee) ; Kouřil, Jan (advisor)
The goal of information extraction is to retrieve relational data from texts written in natural human language. Applications of such obtained information is wide - from text summarization, through ontology creation up to answering questions by QA systems. This work describes design and implementation of a system working in computer cluster which transforms a dump of Wikipedia articles to a set of extracted information that is stored in distributed RDF database with a possibility to query it using created user interface.
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Machine Learning for Natural Language Question Answering
Sasín, Jonáš ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
This thesis deals with natural language question answering using Czech Wikipedia. Question answering systems are experiencing growing popularity, but most of them are developed for English. The main purpose of this work is to explore possibilities and datasets available and create such system for Czech. In the thesis I focused on two approaches. One of them uses English model ALBERT and machine translation of passages. The other one utilizes the multilingual BERT. Several variants of the system are compared in this work. Possibilities of relevant passage retrieval are also discussed. Standard evaluation is provided for every variant of the tested system. The best system version has been evaluated on the SQAD v3.0 dataset, reaching 0.44 EM and 0.55 F1 score, which is an excellent result compared to other existing systems. The main contribution of this work is the analysis of existing possibilities and setting a benchmark for further development of better systems for Czech.
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Chatbot for Smart Cities
Jusko, Ján ; Herout, Adam (referee) ; Zemčík, Pavel (advisor)
The aim of this work is to simplify access to information for citizens of the city of Brno and at the same time to innovate the way of communication between the citizen and his city. The problem is solved by creating a conversational agent - chatbot Kroko. Using artificial intelligence and a Czech language analyzer, the agent is able to understand and respond to a certain set of textual, natural language queries. The agent is available on the Messenger platform and has a knowledge base that includes data provided by the city council. After conducting an extensive user testing on a total of 76 citizens of the city, it turned out that up to 97\% of respondents like the idea of a city-oriented chatbot and can imagine using it regularly. The main finding of this work is that the general public can easily adopt and effectively use a chatbot. The results of this work motivate further development of practical applications of conversational agents.
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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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