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Aplikace procedury Ac4ft-Miner na medicínská data
Nekvapil, Viktor ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
This bachelor thesis deals with the data mining procedure Ac4ft-Miner, implemented in the LISp-Miner system, which is developed at the Department of Information and Knowledge Engineering at the University of Economics, Prague. The aim of this thesis is firstly to describe the procedure in a simple, understandable way. Secondly, the aim is to apply this procedure on the medical data and present examples of use of this procedure. Further aim is to create methodology of use for doctors from the experience obtained. The aims are reached by using a lot of examples, which demonstrate theoretical concepts on concrete data and by the pursuit of the simple visualisation of tasks (analytical questions) solved by the procedure. The output of this thesis is a coherent text with lot of examples separated from the continuous text; so the reader familiar with a particular topic can skip the examples and proceed to the next issue. Further result of this thesis is an outline of the graphical presentation of analytical questions. Both the examples and the graphical presentation will be used further in the SEWEBAR project of which this thesis is one part. The methodology of use of the procedure for doctors is in the form of advices for use of the tool which should contribute to the further research which is needed. This is because of the high complexity of the procedure, which does not allow formulating general conclusions usable in the methodology. Chapter 1 characterizes the overall process of Knowledge Discovery in Databases represented by the CRISP-DM Methodology. Chapter 2 presents theoretical concepts related to Ac4ft-Miner. Chapter 3 deals with action rules. Chapter 4 addresses possibilities of defining the input and interpretation of the output of the Ac4ft-Miner. Chapter 5 describes the research conducted on the real medical data set ADAMEK, states methodology and examples of the output. Chapter 6 summarises the experience obtained and formulates the methodology of use of Ac4ft-Miner for doctors.
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Empirical Comparison of Knowledge Discovery in Databases Systems
Dopitová, Kateřina ; Berka, Petr (advisor) ; Rauch, Jan (referee)
Submitted diploma thesis considers empirical comparison of knowledge discovery in databases systems. Basic terms and methods of knowledge discovery in databases domain are defined and criterions used to system comparison are determined. Tested software products are also shortly described in the thesis. Results of real task processing are brought out for each system. The comparison of individual systems according to previously determined criterions and comparison of competitiveness of commercial and non-commercial knowledge discovery in databases systems are performed within the framework of thesis.
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Utilization of XML databases for retrieval of data-mining specifications
Marek, Tomáš ; Kliegr, Tomáš (advisor) ; Kosek, Jiří (referee)
The aim of this work is to create a querying system in analytical reports stored as PMML documents. These PMML documents are stored in native XML database, because these documents are structured as XML documents. Selected XML database is available for free and its resources and means meet the proposed solution. Also searching algorithm is created to search these documents by means of XQuery language. Inasmuch as searched data have the character of the XML data the use of language for querying XML data suggests. In terms of the use of the XQuery language structure of PMML document was explored and data links in these documents was used to ensure proper search results. Results of the search are association rules from these analytical reports stored in PMML documents, requests of the search are attributes to be in the rules, their values and other limits of the search. So that the whole system is complete and could be fully used, it is necessary to create a communication environment through which the work with stored data is performed. For this purpose, Java and REST(ful) architecture for creating applications are used.
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Analysis of Current Areas of Data Warehouse Solutions
Hník, Pavel ; Pour, Jan (advisor) ; Dvořáková, Dana (referee)
This thesis analyzes various factors of impact on current data warehouse solutions. It is structured along three main sections. The first section dissects current issues faced by data warehouses. The second section focuses on an analysis of how the market for data warehouse solutions has developed; within this context, it also mentions other, related markets. The last section is devoted to current trends in the area of data warehouses and Business Intelligence. While this work focuses on data warehouses proper, the topic is closely interconnected with the overarching category of Business Intelligence, which is why a suitable degree of discussion also of this area appeared to be in order. This paper does not seek to provide advice as to which specific solutions management should choose for their business, nor to serve as a manual on how exactly to implement a data warehouse so as to avoid potential issues. Rather, this thesis attempts to provide a comprehensive and transparent overview of the factors which have impact on today's data warehouse solutions. The rationale behind this thesis is to draw special attention to the key influences on data warehouse solutions at this point in time and to give an informed estimate of their likely future development.
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Knowledge base, analytical questions, LISp-Mner system and ADAMEK data
Kubín, Richard ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
The steps associated with the analytical question solving in terms of LISp-Miner system in ADAMEK medical data are the theme of this thesis. The operating sequence of using 4ft-Miner and SD4ft-Miner procedures in ADAMEK data together with the possibility of further use of formalized background knowledge and preparing routing for automatization of the downrighted steps are the objectiv of this thesis. The summary of the basic concepts and axioms of association rules and GUHA method is the content of the theoretical part of the thesis. Operativ part starts from CRISP-DM methodology. The operating sequence enabling searching for interesting association rules in different data, that is applied on STULONG medical data afterwards in order to get instigations for it's revision, is the produce of this thesis. Used data that come from EuroMISE are concern with cardiological patients.
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Empirical comparison of systems for knowledge discovery in databases
Benešová, Kristýna ; Berka, Petr (advisor) ; Šimůnek, Milan (referee)
S rostoucím množstvím shromažďovaných a ukládaných dat roste také potřeba a zájem majitelů těchto dat o využití jejich potenciálu k dalšímu rozhodování. Proto se vyvíjí nové přístupy a způsoby vycházející z informatiky, statistiky a oblasti strojového učení, které se této potřebě snaží vyhovět. Cílem této diplomové práce je uvést proces dobývání znalostí dat z databází na medicínských datech Tinnitus a představit systémy LISp-Miner a Weka, které daný proces podporují. Obsahem teoretické části diplomové práce je shrnutí základních charakteristik a přístupů procesu dobývání znalostí. Praktická část diplomové práce je věnována realizaci celého procesu v jednotlivých krocích. V samotném kroku modelování jsou využity již zmíněné systémy akademické LISp-Miner a Weka. Poslední část praktické části práce patří prezentaci dosažených výsledků a vlastnímu zhodnocení systémů.
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Empirical comparison of free software suites for knowledge discovery from data
Kasík, Josef ; Berka, Petr (advisor) ; Rauch, Jan (referee)
Both topic and main objective of the diploma thesis is a comparison of free data mining suites. Subjects of comparison are six particular applications developed under university projects as experimental tools for data mining and mediums for educational purposes. Criteria of the comparison are derived from four general aspects that form the base for further analyses. Each system is evaluated as a tool for handling real-time data mining tasks, a tool supporting various phases of the CRISP-DM methodology, a tool capable of practical employment on certain data and as a common software system. These aspects bring 31 particular criteria for comparison, evaluation of whose was determined by thorough analysis of each system. The results of comparison confirmed the anticipated assumption. As the best tool the Weka data mining suite was evaluated. The main advantages of Weka are high number of machine learning algorithms, numerous data preparation tools and speed of processing.
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Data warehouses -- main principles, concepts and methods, tools, applications, design and building of data warehouse solution in real company
Mašek, Martin ; Jelínek, Jiří (advisor) ; Novák, Viktor (referee)
The main goal of this thesis is to summarize and introduce general theoretical concepts of Data Warehousing by using the systems approach. The thesis defines Data Warehousing and its main areas and delimitates Data Warehousing area in terms of higher-level area called Business Intelligence. It also describes the history of Data Warehousing & Business Intelligence, focuses on key principals of Data Warehouse building and explains the practical applications of this solution. The aim of the practical part is to perform the evaluation of theoretical concepts. Based on that, design and build Data Warehouse in environment of an existing company. The final solution shall include Data Warehouse design, hardware and software platform selection, loading with real data by using ETL services and building of end users reports. The objective of the practical part is also to demonstrate the power of this technology and shall contribute to business decision-making process in this company.
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Practical Use of Data Mining Technologies
Uhlíř, Radek ; Pour, Jan (advisor) ; Zajíc, Ján (referee)
This bachelor's thesis maps available technologies of extracting knowledge from the raw data. These methods are globally known as Data Mining. Some of these methods are implemented in the second part - proof of concept of Data mining support in sales department. The aim of this work is to identify and implement suitable technologies for answering analytical questions and getting knowledge from data owned by business companies. It should help to improve and optimize business processes and resource utilization. Customer segmentation support and association rules identification are also expected. In the second part are identified possible weaknesses and problems during the process of implementation and deployment of these systems. The work should propose optimal methods of solving these problems or at least modifications in process of implementation to eliminate some vulnerability. The work is divided into two parts -- first is theoretical and maps available methods and second part is about implementation of project in pharmaceutical company. This solution was built using Microsoft SQL Server platform.
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