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Metody shlukování textových dat / Textual Data Clustering Methods

Clustering of text data is one of tasks of text mining. It divides documents into the different categories that are based on their similarities. These categories help to easily search in the documents. This thesis describes the current methods that are used for the text document clustering. From these methods we chose Simultaneous keyword identification and clustering of text documents (SKWIC). It should achieve better results than the standard clustering algorithms such as k-means. There is designed and implemented an application for this algorithm. In the end, we compare SKWIC with a k-means algorithm.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:237060
Date January 2011
CreatorsMiloš, Roman
ContributorsBurgetová, Ivana, Bartík, Vladimír
PublisherVysoké učení technické v Brně. Fakulta informačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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