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Data Mining Methods for Text Analysis
Kozák, Ondřej ; Marcoň, Petr (referee) ; Dohnal, Přemysl (advisor)
This bachelor thesis explores the current methodology and possibilities of text mining and the subsequent application of some methods. The thesis described methods for preprocessing, methods for converting text to vector space and methods for text analysis and discusses their possible applications. The different preprocessing methods were applied to the text and then the conversion to vector space was demonstrated using simple methods such as BOW, Bag of n-grams, TF-IDF or with machine learning methods which are FastText and GloVe. LSA, LDA, TextRank and cosine similarity methods were applied to the extracted vectors to extract information from the text.
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Computer as an Intelligent Partner in the Word-Association Game Codenames
Jareš, Petr ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
This thesis solves a determination of semantic similarity between words. For this task is used a combination of predictive model fastText and count based method Pointwise Mutual Information. Thesis describes a system which utilizes semantic models for ability to substitue a player in a word association game Codenames. The system has implemented game strategy enabling use of context information from the game progression to benefit his own team. The system is able to substitue a player in both team roles.
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Word Sense Clustering
Hošták, Viliam Samuel ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis deals with semantic similarity of words. It describes and compares existing models that are currently used for this purpose. It discusses the design and implementation of the system for corpus preprocessing, semantic modelling and retrieval of semantically related words. The system that has been created supports the use of distributional semantic models Word2vec, FastText and Glove.
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Sentiment Analysis of Czech and Slovak Social Networks and Web Discussions
Sojka, Matěj ; Dočekal, Martin (referee) ; Smrž, Pavel (advisor)
Thanks to digitalization, the spread of opinions in the population has accelerated sharply in the recent years, however the need to understand them has not changed. The goal of this thesis was to create a system for automatic data collection from social media and web discussions and sentiment analysis in Czech and Slovak language. The system has a web interface for visualizing results and configuring data analysis. The system is capable of offering topics to the user that it considers to occur in the selected data and group posts based on user-defined opinions.
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Fast Adaptation of Codenames Computer Assistant for New Languages
Jareš, Petr ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis extends a system of an artificial player of a word-association game Codenames to easy addition of support for new languages. The system is able to play Codenames in roles as a guessing player, a clue giver or, by their combination a Duet version player. For analysis of different languages a neural toolkit Stanza was used, which is language independent and enables automated processing of many languages. It was mainly about lemmatization and part of speech tagging for selection of clues in the game. For evaluation of word associations were several models tested, where the best results had a method Pointwise Mutual Information and predictive model fastText. The system supports playing Codenames in 36 languages comprising 8 different alphabets.
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Using Word-Association Games for Language Teaching
Babača, Martin ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis explores the use of the word associative game Codenames in language learning, especially learning English as the second language. In order to achieve the goal, it addresses the problem of explaining semantic relations among words. The explanations take advantage of word sketches, provided by the Sketch Engine tool, and of word descriptions available in specialized English dictionaries. The implemented extension of the previously created engine for playing Codenames enables explaining the automatically suggested relations among the hint words and intended words in each game, motivating users for further exploration of the studied language.
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Using Word-Association Games for Language Teaching
Babača, Martin ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This thesis explores the use of the word associative game Codenames in language learning, especially learning English as the second language. In order to achieve the goal, it addresses the problem of explaining semantic relations among words. The explanations take advantage of word sketches, provided by the Sketch Engine tool, and of word descriptions available in specialized English dictionaries. The implemented extension of the previously created engine for playing Codenames enables explaining the automatically suggested relations among the hint words and intended words in each game, motivating users for further exploration of the studied language.
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Data Mining Methods for Text Analysis
Kozák, Ondřej ; Marcoň, Petr (referee) ; Dohnal, Přemysl (advisor)
This bachelor thesis explores the current methodology and possibilities of text mining and the subsequent application of some methods. The thesis described methods for preprocessing, methods for converting text to vector space and methods for text analysis and discusses their possible applications. The different preprocessing methods were applied to the text and then the conversion to vector space was demonstrated using simple methods such as BOW, Bag of n-grams, TF-IDF or with machine learning methods which are FastText and GloVe. LSA, LDA, TextRank and cosine similarity methods were applied to the extracted vectors to extract information from the text.
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Sentiment Analysis of Czech and Slovak Social Networks and Web Discussions
Sojka, Matěj ; Dočekal, Martin (referee) ; Smrž, Pavel (advisor)
Thanks to digitalization, the spread of opinions in the population has accelerated sharply in the recent years, however the need to understand them has not changed. The goal of this thesis was to create a system for automatic data collection from social media and web discussions and sentiment analysis in Czech and Slovak language. The system has a web interface for visualizing results and configuring data analysis. The system is capable of offering topics to the user that it considers to occur in the selected data and group posts based on user-defined opinions.
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