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Text Classification Methods in the Context of Web Pages
Trstenský, Patrik ; Bartík, Vladimír (referee) ; Burget, Radek (advisor)
This work deals with the issue of text classification in the context of websites. It examines available classification methods and their accuracy over web page plain text. It deals with constructing a dataset for training these methods for a specific domain. We obtain data for creating the dataset from publicly available websites that utilize RDF documents defined in HTML code. The conclusion of the work consists of the creation of two datasets for two different domains. Furthermore, the use of these datasets for training models and testing of their accuracy.

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