Extraction of High-Level Semantically Rich Features from Natural Language Text

To represent a text, Natural Language Processing applications are to determine and extract from the text features that are essential for the particular task. Although high-level features seem to be promising for many tasks, they were rarely addressed, since the extraction of those features is a big challenge. This thesis aims at extracting high-level semantically rich features from natural language text. The algorithms we will propose will enable development of novel applications in different areas.

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