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Distributed Sytem for Verification of Properties of Natural Numbers
Tomisová, Martina ; Mírovský, Jiří (advisor) ; Peterek, Nino (referee)
The result of my work is a system for distributed verification of properties of natural numbers. It has two parts - server and client. These communicate via HTTP protocol. The clients perform the computation, the server distributes the work (numbers) and gather results (properties of the given numbers). The input of one computation should be one natural number, as well as the result (output). The distribution can be used for verification of a given property for several natural numbers. Particular jobs can be added to the client as plugins. Two examples of plugins are a part of the work. The first one is very simple and shows how to create plugins. The second example searches for prime numbers (and has it's own arithmetics library for long numbers) - the server can distribute (possibly big) numbers, the client will verify whether a given number is a prime number.
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Artificial Neural Network for Opinion Target Identification in Czech
Glončák, Vladan ; Kuboň, Vladislav (advisor) ; Mírovský, Jiří (referee)
The main focus of this thesis is to use neural networks, specifically long short-term memory cells, for identifying opinion targets in Czech data. The side product is a new version of dataset for opinion target identification. For a comparison, previously obtained results for another languages and by employing probabilistic methods instead were listed. The experiment was successful, achieved results are above trivial baseline models and comparable with the results achieved previously. Powered by TCPDF (www.tcpdf.org)
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Netgraph-A Tool for Searching in the Prague Dependency Treebank 2.0
Mírovský, Jiří
Three sides existed whose connection is solved in this thesis. First, it was the Prague Dependency Treebank 2.0, one of the most advanced treebanks in the linguistic world. Second, there existed a very limited but extremely intuitive search tool - Netgraph 1.0. Third, there were users longing for such a simple and intuitive tool that would be powerful enough to search in the Prague Dependency Treebank. In the thesis, we study the annotation of the Prague Dependency Treebank 2.0, especially on the tectogrammatical layer, which is by far the most complex layer of the treebank, and assemble a list of requirements on a query language that would allow searching for and studying all linguistic phenomena annotated in the treebank. We propose an extension to the query language of the existing search tool Netgraph 1.0 and show that the extended query language satisfies the list of requirements. We also show how all principal linguistic phenomena annotated in the treebank can be searched for with the query language. The proposed query language has also been implemented - we present the search tool as well and talk about the data format for the tool. An attached CD-ROM contains the installation of the tool.
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Development of an Annotation Tool for Universal Dependencies
Storzerová, Tereza ; Zeman, Daniel (advisor) ; Mírovský, Jiří (referee)
The purpose of the work was to develop a user-friendly tool for sentence analysis. It is an application in which the user has the possibility to edit linguistically annotated data, specifically texts annotated according to the Universal Dependencies rules. The application works with the CoNLL-U file format, so you can load such a file and save it later. Visualization clearly and comprehensibly captures the structure and other annotations of a sentence that can be easily edited. The tool also supports file search based on the sentence or word attribute values. The aim of this work was to think about the possibilities how to visualize and modify the data of this kind.
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Artificial Neural Network for Opinion Target Identification in Czech
Glončák, Vladan ; Kuboň, Vladislav (advisor) ; Mírovský, Jiří (referee)
The main focus of this thesis is to use neural networks, specifically long short-term memory cells, for identifying opinion targets in Czech data. The side product is a new version of dataset for opinion target identification. For a comparison, previously obtained results for another languages and by employing probabilistic methods instead were listed. The experiment was successful, achieved results are above trivial baseline models and comparable with the results achieved previously. Powered by TCPDF (www.tcpdf.org)
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Word order reconstruction
Dvořák, Tomáš ; Vidová Hladká, Barbora (advisor) ; Mírovský, Jiří (referee)
A word order reconstruction is a re-arrangement of words to get a gramma- tically correct sentence. It is a very useful task for the applications of natural language processing, machine translation, speech recognition or construction artificial communication partners. We present a corpus-based approach to the task of word order reconstruction. We use two methods: morfological and syntactical method. Both methods use output from the external module. This approach is designed independently on the application where the word order reconstruction can help improve overall performance. Czech and English will be used as the object language. 1
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An Implementation of the Extended Game Quoridor
Trojánek, Tomáš ; Mírovský, Jiří (advisor) ; Zeman, Daniel (referee)
This thesis analyses a classic board game called Quoridor and subsequently its implementation into a form of computer multiplayer application. At first, rules and its extensions from offical version are described, namely - new type of obstacles and generalization of the game board so that it allows bigger amount of players. These specifics alter the game and bring new challenges. A description of algorithms and mathematical study that solves these problems effectively folow. The described version is compared to the original. Finally thesis write about the design, realization and important mechanisms of the application, which contains, among others, implementations of individual algorithms from this text. Program allows to test proved theorems in real environment. It is a network multiplayer game with possibility to add computer oponents.
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Automatic Resolution of Pronoun Coreference in Czech
Košarko, Ondřej ; Mírovský, Jiří (advisor) ; Vidová Hladká, Barbora (referee)
Title: Automatic Resolution of Pronoun Coreference in Czech Author: Ondřej Košarko Department: ÚFAL MFF UK Supervisor: RNDr. Jiří Mírovský, Ph.D. Supervisor's email address: mirovsky@ufal.mff.cuni.cz Abstract: The aim of this thesis is to introduce a procedure for automatic pronomial coreference resolution in Czech texts. The text is morphologically and analytically annotated acording to the system of Prague Dependency Treebank. The procedure uses a machine learning method; for its training a set of manually annotated data from Prague Dependency Treebank is used. Evaluation of the results is also part of this thesis. Keywords: pronomial coreference, automatic resolution, machine learning
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System of Czech numerals and their automatic recognition in texts
Bureš, Jan ; Hlaváčová, Jaroslava (advisor) ; Mírovský, Jiří (referee)
This thesis has two main goals. The first goal is systematic classification of Czech numerals and other quantitative phrases (including multiple-word) with special regard for possible use during automatic recognition of Czech text. The main source of data for theis classification is current Czech grammar and author's research in Czech language corpora The second goal is development of tool for automatic recognition of numerals in Czech text based on the system developed during the first phase of this thesis. This includes determining basic morphological attributes of numerals and their numeric value, where possible and applicable. The tool is even prepared to deal with the fact, that the gramatic rules for numerals are often disregarded.
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Machine Learning Approach to Anaphora Resolution
Novák, Michal ; Žabokrtský, Zdeněk (advisor) ; Mírovský, Jiří (referee)
Anaphora resolution is the key task for some of the Natural Language Processing (NLP) tasks like the information extraction or dialog systems. It can be also valuable in machine translation. All the previous works concerning the anaphora resolution in Czech language mostly focused on the pronoun coreference. Thanks to the recent project of the annotation of extended anaphoric relations in Prague Dependency Treebank 2.0 his work goes further. It attempts to resolve noun phrase coreference, identity-of-sense anaphora and part-whole bridging relations. It has adopted some of the stateof-the-art approaches in the area of machine learning approaches to anaphora resolution, particularly the ranking and the joint anaphor identi cation with the antecedent selection. It introduced a plenty of features and analyzed their contribution on the success rate. The best model of noun phrase coreference achieves the F-score of 39.4%.
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