|
|
Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.
|
|
|
Data Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
|
|
|
Analysis of Mobile Devices Network Communication Data
Abraham, Lukáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
At the beginning, the work describes DNS and SSL/TLS protocols, it mainly deals with communication between devices using these protocols. Then we'll talk about data preprocessing and data cleaning. Furthermore, the thesis deals with basic data mining techniques such as data classification, association rules, information retrieval, regression analysis and cluster analysis. The next chapter we can read something about how to identify mobile devices on the network. We will evaluate data sets that contain collected data from communication between the above mentioned protocols, which will be used in the practical part. After that, we finally get to the design of a system for analyzing network communication data. We will describe the libraries, which we used and the entire system implementation. We will perform a large number of experiments, which we will finally evaluate.
|
|
|
Analysis of Mobile Devices Network Communication Data
Abraham, Lukáš ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
At the beginning, the work describes DNS and SSL/TLS protocols, it mainly deals with communication between devices using these protocols. Then we'll talk about data preprocessing and data cleaning. Furthermore, the thesis deals with basic data mining techniques such as data classification, association rules, information retrieval, regression analysis and cluster analysis. The next chapter we can read something about how to identify mobile devices on the network. We will evaluate data sets that contain collected data from communication between the above mentioned protocols, which will be used in the practical part. After that, we finally get to the design of a system for analyzing network communication data. We will describe the libraries, which we used and the entire system implementation. We will perform a large number of experiments, which we will finally evaluate.
|
|
|
Analýza textů uživatelských recenzí plaveckých bazénů
Dragolovová, Anna
The work focuses on identification of most frequently commented topics in swimming pools user reviews. User reviews have been scrapped from Google review pages, preprocessed to text mining and machine learning compatible format, vectorized by bag of words and word embeddings approaches and analyzed by topic modelling and cluster analysis. Twenty‐two relevant topics indicating swiming pool management priorities have been found as a result.
|
|
|
Data Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
|
|
|
Methodology and problems of data transformation and determine its importance in the integration of heterogeneous information sources
Bartoš, Ivan ; Papík, Richard (advisor) ; Dvořák, Jan (referee) ; Bureš, Miroslav (referee)
Methodology and issues of data transformation and its information value estimation during the integration of the heterogenous information sources PhDr. Ivan BARTOŠ Abstract This study focuses mainly on the data and information transformation issue. This topic is currently critical in several scientific and commercial areas. Information value, information quality and the quality of the source data differs between the various systems. This is not only due to the different topologies of the information sources but also because of its different understanding and a manner of storing the information describing the entity of the enterprise. Such information systems, respectively database systems in the scope of the thesis, could perform well as the stand alone systems. The issue appears in the moment when such heterogeneous systems are required to be integrated and the information shall be migrated between each other. The thesis is logically divided into four major parts based on these issues. The first part describes the methods that can be used to classify the data quality of the source system (the one to be integrated) from which the information can be extracted. Based on assumption of the common lack of project and system documentation hereby introduced methods can be used for such qualification even when the...
|
|
|
Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.
|
|
|
Data Mining in K2 Information System
Figura, Petr ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This project was originated by K2 atmitec Brno s.r.o. company. The result is data mining module in K2 information system environment. Engineered data module implements association analysis over the data of K2 information system data warehouse. Analyzed data contains information about sales filed in K2 information system. Module is implementing consumer basket analysis.
|
|
|
An analysis and implementation of Dashboards within SAP Business Objects 4.0/4.1
Kratochvíl, Tomáš ; Pour, Jan (advisor) ; Šedivá, Zuzana (referee)
The diploma thesis is focused on dashboards analysis and distribution and theirs implementation afterwards in SAP Dashboards and Web Intelligence tools. The main goal of this thesis is an analysis of dashboards for different area of company management according to chosen of architecture solution. Another goal of diploma thesis is to take into account the principles of dashboards within the company and it deals with indicator comparison as well. The author further defines data life cycle within Business Intelligence and deals with the decomposition of particular dashboard types in theoretical part. At the end of theory, it is included an important chapter from point of view data quality, data quality process and data quality improvement and an using of SAP Best Practices and KBA as well for BI tools published by SAP. The implementation of dashboards should be back up theoretical part. Implementation is divided into 3 chapters according to selected architecture, using multisource systems, SAP Infosets/Query and using Data Warehouse or Data Mart as an architecture solution for reporting purposes. The deep implementing section should be help reader to make his own opinion to different architecture, but especially difference in used BI tools within SAP Business Objects. At the end of each section regarding architecture and its solution, there are defined pros and cons.
|
guest ::
