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Pokročilý porovnávač produktov
Prexta, Dávid
This thesis deals with the problem of mining structured information concerning the features of the products from the open text, using open information extraction. These features will make it easier for customers to choose their product. In the beginning, it deals with existing solutions, their shortcomings and analysis of available systems for open information extraction. Furthermore, the theoretical background and technology used in the creation of the system, the design of the system itself and its implementation are discussed. At the end, the system testing, its results and extensions that could be implemented in the future are described.
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DNS Data Analysis for Mobile Device Identification Purposes
Sporni, Alex ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the problem of identification of mobile devices based on DNS data analysis. The thesis provides a theoretical introduction to the computer communication model. This thesis explains the importance of DNS in the terms of network communication between devices, It also presents the provided data sets, which contain real communication of mobile devices. These data sets must be with a suitable technique parsed and stored in a database to provide better data manipulation techniques in the later stages of implementation. This work further describes individual techniques of data processing. It also depicts in detail the methodologies for evaluating the relevance of TF-IDF and the application of cosine similarity to identify the mobile devices. The main output of this work is the evaluation of the achieved results.
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Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
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Searching relevant articles in extensive collections
Vojt, Ján ; Novák, Jiří (advisor) ; Bartoš, Tomáš (referee)
Searching text in articles is usually implemented with fulltext search. Using more advanced techniques however, it is possible to achieve significantly better results. The subject of this work is to create a universal library for searching extensible collections, specialized in czech language. The library makes use of tools capable of working with morphology while considering importance of words. It also conducts an experiment with word pairs, which adds context into the search process. The success rate of this experiment is tried on an extensible collection of data. Created library is a unique tool for processing extensible collections of czech text, while at the same time it is ready for further extension by new languages and methods.
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Events and Places Agregation and Suggestions from Facebook
Dubeň, Matej ; Plchot, Oldřich (referee) ; Szőke, Igor (advisor)
The aim of this bachelor thesis is to explain the design and implementation of an Android application "Let's Go Out", which can recommend Facebook events and places to the user. The recommendation is carried out by using the hybrid recommending system approach that links together the collaborative filtering and a content-based recommendation approach, tracks the user's interaction with the application and, based on recorded data, adapts to the recommendation process. This thesis also describes the testing process that compares the recommender systems of competitive applications and points out achievements.
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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.
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Semantic Similarity of Articles
Veselovský, Martin ; Otrusina, Lubomír (referee) ; Kouřil, Jan (advisor)
This bachelor's thesis deals with modelling of structure of semantic relationships among articles in English language. There are introduced existing methods of articles representation and computation of similarity. The base method is vector space model, which represents document as vector of words. There are given weights of importance to these words using TF-IDF method. Next, there are described advanced methods of modelling, Latent semantic analysis (LSA) and Latent Dirichlet allocation (LDA). This thesis also deals with articles, which are semantically annotated, while weights of annotation words are computed by Stochastic Gradient Descent method. Evaluation of results takes place on the prepared test corpus of documents to which there is reference similarity evaluation.
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Representation of Text and Its Influence on Categorization
Šabatka, Ondřej ; Chmelař, Petr (referee) ; Bartík, Vladimír (advisor)
The thesis deals with machine processing of textual data. In the theoretical part, issues related to natural language processing are described and different ways of pre-processing and representation of text are also introduced. The thesis also focuses on the usage of N-grams as features for document representation and describes some algorithms used for their extraction. The next part includes an outline of classification methods used. In the practical part, an application for pre-processing and creation of different textual data representations is suggested and implemented. Within the experiments made, the influence of these representations on accuracy of classification algorithms is analysed.
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Mining of Textual Data from the Web for Speech Recognition
Kubalík, Jakub ; Plchot, Oldřich (referee) ; Mikolov, Tomáš (advisor)
Prvotním cílem tohoto projektu bylo prostudovat problematiku jazykového modelování pro rozpoznávání řeči a techniky pro získávání textových dat z Webu. Text představuje základní techniky rozpoznávání řeči a detailněji popisuje jazykové modely založené na statistických metodách. Zvláště se práce zabývá kriterii pro vyhodnocení kvality jazykových modelů a systémů pro rozpoznávání řeči. Text dále popisuje modely a techniky dolování dat, zvláště vyhledávání informací. Dále jsou představeny problémy spojené se získávání dat z webu, a v kontrastu s tím je představen vyhledávač Google. Součástí projektu byl návrh a implementace systému pro získávání textu z webu, jehož detailnímu popisu je věnována náležitá pozornost. Nicméně, hlavním cílem práce bylo ověřit, zda data získaná z Webu mohou mít nějaký přínos pro rozpoznávání řeči. Popsané techniky se tak snaží najít optimální způsob, jak data získaná z Webu použít pro zlepšení ukázkových jazykových modelů, ale i modelů nasazených v reálných rozpoznávacích systémech.
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