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Text mining focused on clustering and fuzzy clustering methods
Zubková, Kateřina ; Karpíšek, Zdeněk (referee) ; Žák, Libor (advisor)
This thesis is focused on cluster analysis in the field of text mining and its application to real data. The aim of the thesis is to find suitable categories (clusters) in the transcribed calls recorded in the contact center of Česká pojišťovna a.s. by transferring these textual documents into the vector space using basic text mining methods and the implemented clustering algorithms. From the formal point of view, the thesis contains a description of preprocessing and representation of textual data, a description of several common clustering methods, cluster validation, and the application itself.
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Application of cluster analysis to real data
Onderlička, Tomáš ; Popela, Pavel (referee) ; Žák, Libor (advisor)
This bachelor's thesis deals with finding similar scenarios in the waste management acquired by an optimization tool NERUDA. Cluster analysis, a tool that identifies related objects and classifies them in groups (clusters), is used for this purpose. The aim of this thesis is to review basic algorithms of cluster analysis and to develop a software that implements them. The software is then used to cluster real data from NERUDA which is followed by an assessment of the obtained clusters.
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Cluster Analysis Module of a Data Mining System
Riedl, Pavel ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis deals with development of a module for a data mining system, which is being developed on FIT. The first part describes the general knowledge discovery process and cluster analysis including cluster validation; it also describes Oracle Data Mining including algorithms, which it uses for clustering. At the end it deals with the system and the technologies it uses, such as NetBeans Platform and DMSL. The second part describes design of a clustering module and a module used to compare its results. It also deals with visualization of cluster analysis results and shows the achievements.
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Text mining focused on clustering and fuzzy clustering methods
Zubková, Kateřina ; Karpíšek, Zdeněk (referee) ; Žák, Libor (advisor)
This thesis is focused on cluster analysis in the field of text mining and its application to real data. The aim of the thesis is to find suitable categories (clusters) in the transcribed calls recorded in the contact center of Česká pojišťovna a.s. by transferring these textual documents into the vector space using basic text mining methods and the implemented clustering algorithms. From the formal point of view, the thesis contains a description of preprocessing and representation of textual data, a description of several common clustering methods, cluster validation, and the application itself.
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|
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Application of cluster analysis to real data
Onderlička, Tomáš ; Popela, Pavel (referee) ; Žák, Libor (advisor)
This bachelor's thesis deals with finding similar scenarios in the waste management acquired by an optimization tool NERUDA. Cluster analysis, a tool that identifies related objects and classifies them in groups (clusters), is used for this purpose. The aim of this thesis is to review basic algorithms of cluster analysis and to develop a software that implements them. The software is then used to cluster real data from NERUDA which is followed by an assessment of the obtained clusters.
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|
|
Cluster Analysis Module of a Data Mining System
Riedl, Pavel ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis deals with development of a module for a data mining system, which is being developed on FIT. The first part describes the general knowledge discovery process and cluster analysis including cluster validation; it also describes Oracle Data Mining including algorithms, which it uses for clustering. At the end it deals with the system and the technologies it uses, such as NetBeans Platform and DMSL. The second part describes design of a clustering module and a module used to compare its results. It also deals with visualization of cluster analysis results and shows the achievements.
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