|
|
Data Mining Based Web Analyzer of Job Advertisements
Wittner, Alex ; Dzurenda, Petr (referee) ; Sikora, Marek (advisor)
Cílem této bakalářské práce bylo vytvoření automatizovaného zadávání nových pracovních inzerátů pomocí vložení URL v rámci již existující webové aplikace https://rewire.informacni-bezpecnost.cz, jejíž cílem je shromažďování pracovních inzerátů v oblasti cybersecurity s podrobnou analýzou pracovních kompetencí. Pracovní inzeráty jsou analyzovány pomocí více vzorového vyhledávacího algoritmu Aho-Corasick, psaného v jazyce Java. K získávání informací ze zadaných pracovních inzerátů slouží Python skript využívající knihovnu Selenium. Výsledná implementace a webová stránka je vytvořena pomocí jazyka PHP a knihovny ReactJS využívající JavaScript.
|
|
|
Knowledge Discovery from Spatio-Temporal Data
Liptáková, Daša ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
This thesis deals with knowledge discovery from spatio-temporal data. Firstly, it describes the general principles of knowledge discovery and then knowledge discovery from spatio-temporal data, where it mainly focuses on methods for detecting outlying trajectories of moving objects. In the next section, the thesis describes the design and implementation of the mining task and demonstration application. Finally, several experiments are performed over three different datasets.
|
|
|
Use of Data Mining in Company Processes
Měchura, Dalibor ; Kříž, Jiří (referee) ; Luhan, Jan (advisor)
This masters thesis focuses on data mining techniques and business intelligence analysis. In accordance with the analysis of the current situation in the company, a complementary solution to the problem is proposed and a view of the existing data is provided from a different perspective, namely using RapidMiner. The output of the thesis is thus concrete analytical outputs for decision support in the company.
|
|
|
Modelling and Analysis of Logistics Processes by Applying Process and Data Mining Techniques
Rudnitckaia, Julia ; Wang, Hao (referee) ; Zendulka, Jaroslav (referee) ; Hruška, Tomáš (advisor)
In this thesis, we propose an approach for modelling hidden and unknown processes and subprocesses in the example of a seaport logistics area. Having the underlying process model makes it possible to exploit more advanced algorithms since deviations and main paths are becoming visible and better controlled. The obtained model is the foundation for the core research of this work and will be enriched with key performing indicators and their forecast by applying advanced process mining, statistics, and machine learning techniques. The main difference of the approach is that we take as a target variable not any specific value, but the object - a process variant or a process type with a set of parameters. Bottleneck analysis, from one side, and predictive analysis, on the other hand, are enforced with context-aware information, especially with these additional objective process attributes. Furthermore, the support of the descriptive ("As is") current process model with certain notation and the integration with relevant bottleneck and predictive methods compromise the advantages of the approach. The work primarily focuses on the design of algorithms and methods for supporting logistics data analysis. However, it can be adjusted and applied to other areas accordingly, which makes the approach flexible and versatile. The result of the work is the framework for unstructured process modelling and the key process parameters predictive method. This analysis of processes with their attributes might be used for decision-making systems and process maps in future.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
guest ::
