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Association Rules Mining over Data Warehouses
Hlavička, Ladislav ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This thesis deals with association rules mining over data warehouses. In the first part the reader will be familiarized with terms like knowledge discovery in databases and data mining. The following part of the work deals with data warehouses. Further the association analysis, the association rules, their types and mining possibilities are described. The architecture of Microsoft SQL Server and its tools for working with data warehouses are presented. The rest of the thesis includes description and analysis of the Star-miner algorithm, design, implementation and testing of the application.
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Mining Multiple Level Association Rules
Nachtnebl, Viktor ; Stryka, Lukáš (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery from data scope is quite a young concept but is becoming more and more popular. This bachelor's thesis is engaged in mining multiple level association rules. There are four different methods of investigation discussed. These offer an insight into the problem of concept and implementation of application. At the end we have confronted and reviewed the results of these four algorithms.
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Web Page Classification
Kolář, Roman ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This paper presents problem of automatic webpages classification using association rules based classifier. Classification problem is presented, as a one of datamining technique, in context of mining knowledges from text data. There are many text document classification methods presented with highlighting benefits of classification methods using association rules. The main goal of work is adjusting selected classification method for relation data and design draft of webpages classifier, which classifies pages with the aid of visual properties - independent section layout on the web page, not (only) by textual data. There is also ARC-BC classification method presented as a selected method and as one of intriguing classificators, that derives accuracy and understandableness benefits of all other methods.
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Data Mining
Slezák, Milan ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
The thesis is focused on an introduction of data mining. Data mining is focused on finding of a hidden data correlation. Interest in this area is dated back to the 60th the 20th century. Data analysis was first used in marketing. However, later it expanded to more areas, and some of its options are still unused. One of methodologies is useful used for creating of this process. Methodology offers a concise guide on how you can create a data mining procedure. The data mining analysis contains a wide range of algorithms for data modification. The interest in data mining causes that number of data mining software is increasing. This thesis contains overviews some of this programs, some examples and assessment.
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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.
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Web Page Classification
Kolář, Roman ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This paper presents problem of automatic webpages classification using association rules based classifier. Classification problem is presented, as a one of datamining technique, in context of mining knowledges from text data. There are many text document classification methods presented with highlighting benefits of classification methods using association rules. The main goal of work is adjusting selected classification method for relation data and design draft of webpages classifier, which classifies pages with the aid of visual properties - independent section layout on the web page, not (only) by textual data. There is also ARC-BC classification method presented as a selected method and as one of intriguing classificators, that derives accuracy and understandableness benefits of all other methods.
|
|
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Mining Multiple Level Association Rules
Nachtnebl, Viktor ; Stryka, Lukáš (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery from data scope is quite a young concept but is becoming more and more popular. This bachelor's thesis is engaged in mining multiple level association rules. There are four different methods of investigation discussed. These offer an insight into the problem of concept and implementation of application. At the end we have confronted and reviewed the results of these four algorithms.
|
|
|
Association Rules Mining over Data Warehouses
Hlavička, Ladislav ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This thesis deals with association rules mining over data warehouses. In the first part the reader will be familiarized with terms like knowledge discovery in databases and data mining. The following part of the work deals with data warehouses. Further the association analysis, the association rules, their types and mining possibilities are described. The architecture of Microsoft SQL Server and its tools for working with data warehouses are presented. The rest of the thesis includes description and analysis of the Star-miner algorithm, design, implementation and testing of the application.
|
|
|
Data Mining
Slezák, Milan ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
The thesis is focused on an introduction of data mining. Data mining is focused on finding of a hidden data correlation. Interest in this area is dated back to the 60th the 20th century. Data analysis was first used in marketing. However, later it expanded to more areas, and some of its options are still unused. One of methodologies is useful used for creating of this process. Methodology offers a concise guide on how you can create a data mining procedure. The data mining analysis contains a wide range of algorithms for data modification. The interest in data mining causes that number of data mining software is increasing. This thesis contains overviews some of this programs, some examples and assessment.
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Association rule visualization in web environment
Škrabal, Radek ; Hazucha, Andrej (advisor) ; Kuchař, Jaroslav (referee)
The aim of this thesis is to implement a web interface for the LISp-Miner academic system which provides association rule mining capability. There is a new trend these days for knowledge discovery in databases applications which are being transformed from desktop applications to web applications and this arises both new opportunities and issues. This thesis describes new interactive approach for association rule mining in which the user is an essential part of the algorithm and can alter the task setting. Users can also collaborate by creating domain knowledge repository which helps finding new interesting information out of the data.
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