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Feature extraction from image data
Uher, Václav ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image processing is one area of signal analysis. This thesis is involved in feature extraction from image data and its implementation using Java programming language. The main contribution of this thesis lies in develop features extractors and their implementation in the program RapidMiner. The result is a robust tool for image analysis. The functionality of each operator is tested on mammogram images. A function model was developed for the removal of artifacts from the mammography images. The success rate of removal is comparable with other similar works. Furthermore, learning algorithms were compared on example detection of ventricle in ultrasound image.
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Data Mining in Social Networks
Raška, Jiří ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
This thesis deals with knowledge discovery from social media. This thesis is focused on feature based opinion mining from user reviews. In theoretical part were described methods of opinion mining and natural language processing. Main parts of this thesis were design and implementation of library for opinion mining based on Stanford Parser and lexicon WordNet. For feature identi cation was used dependency grammar, implicit features were mined with method CoAR and opinions were classi ed with supervised algorithm. Finally were given experiments with implemented library and examples of usage.
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Implementation of Mining Modules of Data Mining System on NetBeans Platform
Stríž, Rostislav ; Bartík, Vladimír (referee) ; Šebek, Michal (advisor)
Data collecting plays an important role in many aspects of today's businesses and quality information is the key to success. Process called Knowledge Discovery in Databases makes possible to extract hidden information that can be used further in our efforts. Main goal of this thesis is to describe an addition to such Data Mining System. Main objective is to create data mining module for NetBeans application, developed for demonstrational purposes by Faculty of Information Technology. New module is going to be able to mine information from Oracle database server via unusual use of Genetic Algorithm. This thesis describes the whole process of module implementation, begining with theoretical basics through coding details to final testing and summary.
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Multi-Label Classification of Text Documents
Průša, Petr ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
The master's thesis deals with automatic classifi cation of text document. It explains basic terms and problems of text mining. The thesis explains term clustering and shows some basic clustering algoritms. The thesis also shows some methods of classi fication and deals with matrix regression closely. Application using matrix regression for classifi cation was designed and developed. Experiments were focused on normalization and thresholding.
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Knowledge Discovery from Time Series
Krutý, Peter ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This thesis is focused on the field of knowledge discovery from data, specifically from time series. Main objective is to research Python programming language support in this area and then design and implement an application that will allow to demonstrate and compare selected methods. Methods are demonstrated in experiments using appropriate data set. The output of the thesis is a comparison of methods for specific tasks and the application implementing selected methods.
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Algorithm for Product Recommendation
Bodeček, Miroslav ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The goal of this project is to explore the problem of product recommendations in the area of e-commerce and to evaluate known techniques, design product recommendation system for an existing e-commerce site, implement it and test it. This report introduces the problem, briefly examines current state of affairs in this area and defines requirements for a product recommendation module. The concept of data mining in general is introduced. The report proceeds to present detailed design corresponding to defined requirements and summarizes data gathered during testing phase. It concludes with evaluation and with discussion of the remaining goals for this thesis.
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Multidimensional Data Analysis and Analytic View Processing
Foltýnová, Veronika ; Burget, Radim (referee) ; Škorpil, Vladislav (advisor)
This thesis deals with the analysis and display of multidimensional data. In the theoretical part, the issue of data mining, its tasks and techniques, and a brief explanation of the terms Business Intelligence and data warehouse are presented. The issue of databases is also described in this thesis. Subsequently, the options for displaying multidimensional data are described. At the end of the theoretical part is briefly explained the problems of optical networks and especially the terms Gigabit passive optical network and its frame, because the data from the frames of this network will be displayed by an application. In the practical part, you can find creating a source database and an application to create a OLAP cube and display multidimensional data. This application is based on the theoretical knowledge of multidimensional databases and OLAP technology.
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Analysis and Structure Recommendations for E-commerce Site Optimization
Bureš, Petr ; Hudák, Michal (referee) ; Dydowicz, Petr (advisor)
This bachelor‘s thesis focuses on analysis of optimization of e-commerce website. The aim of this work is to outline the optimization solutions from different point of views including online marketing, information architecture, web analytics and other weak points identified by the analysis. Several approaches of methodology will be used to support the analysis, such as data mining analysis of a shopping basket integrated within e-commerce website. The economic benefits of the final optimisation solutions will be assessed and the recommendations will be set out.
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Competitive Intelligence
Mikuš, Ondřej ; Karásek, Jan (referee) ; Bartes, František (advisor)
The diploma thesis focuses on the practical use of competitive intelligence, a method increasingly used to support decision making nowadays. The essential key principle is based on collection of precise data and their thourough analysis. The obtained information gives a comprehensive overview of the competitor analysis. The acquired knowledge of the competition is important for company's strategic decision-making processes. At the beginning the thesis gives a theoretical background on different means of data collecting including the ethic kodex. Folowing is the identification of the modern sources of information. Further, various methods and approaches of competitive intelligence are described. And the theoretical background on competitive strategies and their impact on the market wraps up the theoretical part of the thesis. The method is applied to create departmet of competitive inteligence for the company. Then the various options for further go to market activities are described and the scope of cooperation with selected customers is evaluted. The thesis describes the competitive intelligence advantages and the possible ways of aplications for the competitive strategy. At the end, the recommendations for the management of the company are summed up.
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Mining Multiple Level Association Rules
Nguyenová, Thanh Lam ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with multiple level association rules mining. The aim of this work is to focus on available algorithms for mining multiple level association rules and to implement an application with a graphical user interface that will demonstrate the functionality of these algorithms. Five algorithms based on the Apriori algorithm were chosen. Experiments with each algorithm were performed using the application and the results were compared and evaluated at the end of the thesis.
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