|
|
Automated Detection of Hate Speech and Offensive Language
Štajerová, Alžbeta ; Žmolíková, Kateřina (referee) ; Fajčík, Martin (advisor)
This thesis discusses hate speech and offensive language phenomenon, their respective definitions and their occurrence in natural language. It describes previously used methods of solving the detection. An evaluation of available data sets suitable for the problem of detection is provided. The thesis aims to provide additional methods of solving the detection of this issue and it compares the results of these methods. Five models were selected in total. Two of them are focused on feature extraction and the remaining three are neural network models. I have experimentally evaluated the success of the implemented models. The results of this thesis allow for comparison of the typical approaches with the methods leveraging the newest findings in terms of machine learning that are used for the classification of hate speech and offensive language.
|
|
|
Deep Neural Networks Used for Customer Support Cases Analysis
Marušic, Marek ; Ryšavý, Ondřej (referee) ; Pluskal, Jan (advisor)
Umelá inteligencia je pozoruhodne populárna v dnešnej dobe, pretože si dokáže poradiť s rôznymi veľmi komplexnými úlohami v odvetviach ako napr. spracovanie obrazu, spracovanie zvuku, spracovanie prirodzeného jazyka a podobne. Keďže Red Hat doteraz už vyriešil obrovksé množstvo zákazníckych požiadavkov počas podpory rôznych produktov. Preto bola navrhnutá myšlienka použiť umelú inteligenciu práve na tieto dáta a docieliť tak zlepšenie a zrýchlenie procesu riešenia zákaznícky požiadavkov. V tejto práci sú popísané použité techniky na spracovanie týchto dát a úlohy, ktoré je možné riešiť pomocou hlbokých neurónových sietí. Taktiež sú v tejto práci popísane rôzne modely, ktoré boli vytvorené počas riešenia tejto práce a snažia sa adresovať rôzne úlohy. Ich výkony sú porovnané na spomínaných úlohách.
|
|
|
Determination of basic form of words
Šanda, Pavel ; Burget, Radim (referee) ; Karásek, Jan (advisor)
Lemmatization is an important preprocessing step for many applications of text mining. Lemmatization process is similar to the stemming process, with the difference that determines not only the word stem, but it´s trying to determines the basic form of the word using the methods Brute Force and Suffix Stripping. The main aim of this paper is to present methods for algorithmic improvements Czech lemmatization. The created training set of data are content of this paper and can be freely used for student and academic works dealing with similar problematics.
|
|
|
Text document plagiarism detector
Kořínek, Lukáš ; Horák, Karel (referee) ; Petyovský, Petr (advisor)
This diploma thesis is concerned with research on available methods of plagiarism detection and then with design and implementation of such detector. Primary aim is to detect plagiarism within academic works or theses issued at BUT. The detector uses sophisticated preprocessing algorithms to store documents in its own corpus (document database). Implemented comparison algorithms are designed for parallel execution on graphical processing units and they compare a single subject document against all other documents within the corpus in the shortest time possible, enabling near real-time detection while maintaining acceptable quality of output.
|
|
|
Web Application for Intuitive Composition of Text Filters
Sadílek, Jakub ; Kolář, Martin (referee) ; Herout, Adam (advisor)
The aim of this thesis is to provide intuitive and easy to use tool for advanced text filtration with the option of easy prototyping and tuning, without the necessity to know programming techniques. The basic principle is the choice of text tools and their inserting into the sequence, so called pipeline, which is typical for shell, from which the application draws inspiration. Tools can be also additionally edited or swapped. The application is aimed primarily at users unfamiliar with this principle or at programmers, for whom it is time-efficient to have their text modified this way and afterwards generate equivalent shell expression. Another way of tuning is realized using so called breakpoints, through which it is easy to quickly focus on chosen lines of the text. This way, the application offers functionality in two separated modes, between which the users can switch anytime according to their needs.
|
|
|
Classification Framework
Koroncziová, Dominika ; Otrusina, Lubomír (referee) ; Kouřil, Jan (advisor)
The goal of this work is the design and implementation of a machine learning software, based on the RapidMiner library. The finished application integrates the most commonly used algorithms and processes implemented in RapidMiner into an easily usable program. The application contains a simple command line interface, as well as a graphic interface to simplify selection of multiple parameters. The program also provides a tool to create standalone programs, that can be used for classification with a pre-trained model. On top of the original requirements the possibility to work with textual data from Wikipedia was also implemented, providing a tool for downloading and preprocessing of the data in order to use them as training input. This text focuses on the specifics of the algorithms and classifiers used and on their features and uses, and describes the design and implementation of the system. As part of this work, several tests were run in order to validate the efficiency and functionality of the program. The test results are included at the end of the thesis.
|
|
|
Recognition of emotions in text using artificial intelligence
Vylíčil, Radek ; Karásek, Jan (referee) ; Mašek, Jan (advisor)
This thesis deals with the recognition of emotions from text using machine learning. The text describes methods how to train and test an recognition models. The main contribution of this thesis consists in creation decision tree in Java programming language. Created algorithm was integrated as plugin into the RapidMiner tool. The thesis contains some created examples for executing in RapidMiner. The functionality of decision tree was demonstrated on created database.
|
|
|
Shlukování textových dokumentů a jejich částí
Zápotocký, Radoslav ; Kopecký, Michal (advisor) ; Skopal, Tomáš (referee)
This thesis analyses use of vector-space model and data clustering approaches on parts of single document - on chapters, paragraphs and sentences - to allow simple navigation between similar parts. A simulation application (SimDIS), written in C# programming language is also part of this thesis. The application implements the described model and provides tools for visualization of vectors and clusters.
|
|
|
Shlukování textových dokumentů a jejich částí
Zápotocký, Radoslav ; Kopecký, Michal (advisor) ; Skopal, Tomáš (referee)
This thesis analyses use of vector-space model and data clustering approaches on parts of single document - on chapters, paragraphs and sentences. A simulation application (SimDIS), written in C# programming language is also part of this thesis. The application implements the adjusted model and provides tools for visualization of vectors and clusters.
|
|
|
Text Document Plagiarism Detector
Kořínek, Lukáš
This paper provides an overview of diploma thesis concerned with research on availablemethods of plagiarism detection and then with design and implementation of such detector. Primaryaim is to detect plagiarism within academic works or theses issued at BUT. The detector uses sophisticatedpreprocessing algorithms to store documents in its own NoSQL corpus. Implementedcomparison algorithms are designed for parallel execution on graphical processing units and theycompare a single subject document against all other documents within the corpus in the shortest timepossible, enabling near real-time detection capabilities.
|
guest ::
