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Acquiring Thesauri from Wikipedia
Novák, Ján ; Schmidt, Marek (referee) ; Otrusina, Lubomír (advisor)
This thesis deals with automatic acquiring thesauri from Wikipedia. It describes Wikipedia as a suitable data set for thesauri acquiring and also methods for computing semantic similarity of terms are described. The thesis also contains a description of concepts and implementation of the system for automatic thesauri acquiring. Finally, the implemented system is evaluated by the standard metrics, such as precision or recall.
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Quality Analysis of Electronic Dictionaries Transformation
Stehlíková, Petra ; Škoda, Petr (referee) ; Kouřil, Jan (advisor)
The bachelor's thesis deals with electronic dictionaries, their formats and quality analysis of their conversions. The thesis describes Lexical Markup Framework format in detail. It also discusses the capabilities of advanced algorithms such as LSA for conversion quality analysis and the tools that can be used for the analysis. Based on this theoretical knowledge the scripts in Python language were created to analyze dictionaries in Lexical Markup Framework format.
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Methods of Document Summarization on the Web
Belica, Michal ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
The work deals with automatic summarization of documents in HTML format. As a language of web documents, Czech language has been chosen. The project is focused on algorithms of text summarization. The work also includes document preprocessing for summarization and conversion of text into representation suitable for summarization algorithms. General text mining is also briefly discussed but the project is mainly focused on the automatic document summarization. Two simple summarization algorithms are introduced. Then, the main attention is paid to an advanced algorithm that uses latent semantic analysis. Result of the work is a design and implementation of summarization module for Python language. Final part of the work contains evaluation of summaries generated by implemented summarization methods and their subjective comparison of the author.
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Semantic Similarity of Terms
Novák, Ján ; Šilhavá, Jana (referee) ; Schmidt, Marek (advisor)
The goal of this thesis is processing knowledge about Automatic Term Recognition and methods of computing term similarity according to co-occurence and on ground of this knowledge suggest and implement system for computing semantic similarity of terms from large collection of documents.
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Semantic Similarity of Texts
Bradáč, Václav ; Otrusina, Lubomír (referee) ; Smrž, Pavel (advisor)
This paper deals with the determination of semantic similarity texts, focusing on scalability. Part of treatment is a theoretical overview of the tools to implement the system on test data. Tested corpus contains expert articles in the English language. The aim is to analyze these articles, modified to facilitate the analysis of their semantic analogues. One of the most utilized tools is a representation of data in a vector space model.
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Application for Text Summarization
Mička, Jakub ; Zendulka, Jaroslav (referee) ; Bartík, Vladimír (advisor)
This work is focused on an implementation a web application, which is a tool for automatic English text summarization. In result, automatic text summarization is made by TextRank and Latent semantic analysis method. Both of these methods are improved by named entity recognition. The main benefit of this work is proving that using the named entity recognition with Latent semantic analysis and especially with TextRank method leads to creation of higher quality summaries. This quality of the summaries was verified by ROUGE metrics.
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Získávání skrytých znalostí z online dat souvisejících s vysokými školami
Hlaváč, Jakub
Social networks are a popular form of communication. They are also used by universities in order to simplify information providing and addressing candidates for study. Foreign study stays are also a popular form of education. Students, however, encounter a number of obstacles. The results of this work can help universities make their social network communication more efficient and better support foreign studies. In this work, the data from Facebook related to Czech universities and the Erasmus program questionnaire data were analyzed in order to find useful knowledge. The main emphasis was on textual content of communication. The statistical and machine learning methods, including mostly feature selection, topic modeling and clustering were used. The results reveal interesting and popular topics discussed on Czech universities social networks. The main problems of students related to their foreign studies were identified too and some of them were compared for countries and universities.
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Quality Analysis of Electronic Dictionaries Transformation
Stehlíková, Petra ; Škoda, Petr (referee) ; Kouřil, Jan (advisor)
The bachelor's thesis deals with electronic dictionaries, their formats and quality analysis of their conversions. The thesis describes Lexical Markup Framework format in detail. It also discusses the capabilities of advanced algorithms such as LSA for conversion quality analysis and the tools that can be used for the analysis. Based on this theoretical knowledge the scripts in Python language were created to analyze dictionaries in Lexical Markup Framework format.
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Application for Text Summarization
Mička, Jakub ; Zendulka, Jaroslav (referee) ; Bartík, Vladimír (advisor)
This work is focused on an implementation a web application, which is a tool for automatic English text summarization. In result, automatic text summarization is made by TextRank and Latent semantic analysis method. Both of these methods are improved by named entity recognition. The main benefit of this work is proving that using the named entity recognition with Latent semantic analysis and especially with TextRank method leads to creation of higher quality summaries. This quality of the summaries was verified by ROUGE metrics.
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Utilization of latent semantic analysis in virtual screening
Kolář, Jiří ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Title: Utilization of latent semantic analysis in virtual screening Author: Jiří Kolář Department: Department of Software Engineering Supervisor: RNDr. David Hoksza, Ph.D., Department of Software Engineering Abstract: Aim of this thesis is to investigate utilisation of latent semantic in- dexing in Virtual screening. We have examined existing VS method called lat- ent semantic structural indexing (LaSSI) and compared performance of different structural fingerprints. Additionally, we have developed a new model that com- pare fragments of molecules by usage of latent semantic indexing. Fragments are characterized by formula based counts and descriptors describing the physi- cochemical properties. Results of our methods are compared to VS techniques using directly standard fingerprints. Keywords: virtual screening cheminformatics ligand-based fingerprints ECFP TT latent semantic analysis LaSSI iii
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