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Adapting Data Mining for German Named Entity Recognition
Abstract
In the latest decades, machine learning approaches have been intensively experimented for natural language processing. Most of the time, systems rely on using statistics within the system, by analyzing texts at the token level and, for labelling tasks, categorizing each among possible classes. One may notice that previous symbolic approaches (e.g. transducers) where designed to delimit pieces of text. Our research team developped mXS, a system that aims at combining both approaches. It locates boundaries of entities by using sequential pattern mining and machine learning. This system, intially developped for French, has been adapted to German.
Publikationstyp
ConferencePaper
Autor*in •
Nouvel, Damien
Antoine, Jean-Yves
Erscheinungsdatum
2014
Fachbereich
Institut / Einrichtung
Erschienen in
Workshop proceedings of the 12th edition of the KONVENS conference
Erste Seite
149
Letzte Seite
152
URN
urn:nbn:de:gbv:hil2-opus-3095
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