National Repository of Grey Literature 43 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Measurement of (anti)immigration Attitudes from the Methodological Perspective. Quality of Measurement with the Special Focus on Measurement Equivalence
Šarapatková, Anna ; Remr, Jiří (advisor) ; Soukup, Petr (referee)
Opportunities that we have in today's world are sharply evolving, and the world is changing all together with these changes. This development is noticeably observed within the topic of global movement of (not only) population, which has changed fundamentally, both economically, politically and socially. Today's so much diversified form of migration, which has lost its transparency it used to has, is a very up to date and debated topic currently almost all over the world. Because of high importance of the topic "migration" it is often subject of research and number of surveys. One of the most examined area within the topic migration is attitudes of people towards immigration and immigrant, oftentimes together with investigating cause leading to particular attitude. Due to the international reach of the topic, these attitudes are often subject of cross-national research or national research, which, however, use data from international surveys. There is a clear disparity across European states in these attitudes towards immigration and, above all, the immigrants themselves. Given this nature of cross-national surveys measuring attitudes towards immigrants, it is important to focus on the measurement quality, which is becoming increasingly complex in the perspective of international research. It is...
Converting HTML product data to Linked Data
Kadleček, Rastislav ; Nečaský, Martin (advisor) ; Svoboda, Martin (referee)
In order to make a step towards the idea of the Semantic Web it is necessary to research ways how to retrieve semantic information from documents published on the current Web 2.0. As an answer to growing amount of data published in a form of relational tables, the Odalic system, based on the extended TableMiner+ Semantic Table Interpretation algorithm was introduced to provide a convenient way to semantize tabular data using knowledge base disambiguation process. The goal of this thesis is to propose an extended algorithm for the Odalic system, which would allow the system to gather semantic information for tabular data describing products from e-shops, which have very limited presence in the knowl- edge bases. This should be achieved by using a machine learning technique called classification. This thesis consists of several parts - obtaining and preprocessing of the product data from e-shops, evaluation of several classification algorithms in order to select the best-performing one, description of design and implementation of the extended Odalic algorithm, description of its integration into the Odalic system, evaluation of the improved algorithm using the obtained product data and semantization of the product data using the new Odalic algorithm. In the end, the results are concluded and possible...
Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
Computer-aided data quality monitoring and assessment in clinical research
Šiška, Branislav ; Kolářová, Jana (referee) ; Schwarz, Daniel (advisor)
The diploma thesis deals with the monitoring and evaluation of data in clinical research. Usual methods to identify incorrect data are one-dimensional statistical methods per each variable in the register. Proposed method enters directly into database and finds out outliers in data using machine learning combined with multidimensional statistical methods that transform all column variables of clinical register to one, representing one record of patient in the register. Algorithm of proposed method is written in Matlab.
Data quality and consistency in Scopus and Web of Science in their indexing of Czech Journals
Mika, Pavel ; Szarzec, Jakub ; Sivertsen, Gunnar
This study addresses the discussion of “quality versus coverage” that often arises if a choice is needed between Scopus and Web of Science (WoS). We present a new methodology to detect problems in the quality of indexing procedures. Our preliminary findings indicate the same degree and types of errors in Scopus and WoS. The more serious errors seem to occur in the indexing of cited references, not in the recording of traditional metadata.
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Implementace Business Intelligence v MVNO
Kamenchshikova, Alena ; Pour, Jan (advisor) ; Basl, Josef (referee)
The goal of this paper is to implement Business Intelligence solution for mobile virtual network operator Erbia Mobile. The first part is devoted to description and analysis of concepts and architecture associated with BI implementation. The second part deals with technical aspects of BI introduction to the company based on listed requirements gathered from series of interviews with management. Implementation is initiated by analysis of company data sources and detailed description of attributes essential to the telecommunication industry. Based on requirements and data source examination outputs, multidimensional analysis is created and described in detail. Next part describes individual components (Data Warehouse, ETL, OLAP cubes) implementation as well as different optimization techniques. Given components created on Microsoft platform using Integration, Analysis and Reporting Services. Final reports and dashboard visualizations are created using MS Excel and Power BI software tools.
Data quality and its analysis in a non-bank loan company
Vránek, Pavel ; Maryška, Miloš (advisor) ; Espinoza, Felix (referee)
This bachelor thesis is focused on complex elaboration of the subject data quality from the theoretical description of working with data in an information system, through the data quality definition, description of the causes of poor quality of data and consequences, which poor data quality brings, to analyze the quality of data in the non-bank load company. For the analysis of the data quality will be first selected suitable dimensions of data quality, for which will be subsequently defined metrics. These metrics will be then measured over a real data using SQL query language and software designed for the analysis of data quality. The main contribution of this work is complex processing of data quality issues and a demonstration of the real state of data quality in the non-bank loan company. The work offers the possibility of extending the draft procedures and rules for data quality management.
Effectivity assessment of the implementation of the reporting system
Řežábek, Martin ; Lorenc, Miroslav (advisor) ; Vladyka, Štěpán (referee)
Thesis is focused on effectivity assessment of the reporting system of the selected company and the comparison of the former and current reporting solution. This is achieved by the appropriate literature research, creation of the individual assessment model based on the methodology of the analogy from the information systems assessment and based on the experience of the selected company's employees and the experience of the experts in the field of corporate financial management with the focus on the reporting systems. Model is defined by the set of criteria structured into the groups and by the weights assigned to criteria along with the value for each of them. The last phase consists of stepping out of the individual assessment and defines the generally applicable model, usable on the wide range of different reporting systems.
Data comparability in knowledge discovery in databases
Horáková, Linda ; Chudán, David (advisor) ; Svátek, Vojtěch (referee)
The master thesis is focused on analysis of data comparability and commensurability in datasets, which are used for obtaining knowledge using methods of data mining. Data comparability is one of aspects of data quality, which is crucial for correct and applicable results from data mining tasks. The aim of the theoretical part of the thesis is to briefly describe the field of knowledqe discovery and define specifics of mining of aggregated data. Moreover, the terms of comparability and commensurability is discussed. The main part is focused on process of knowledge discovery. These findings are applied in practical part of the thesis. The main goal of this part is to define general methodology, which can be used for discovery of potential problems of data comparability in analyzed data. This methodology is based on analysis of real dataset containing daily sales of products. In conclusion, the methodology is applied on data from the field of public budgets.

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