Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-10471
Authors: Sabbatino, Valentino
Title: Automatic recognition of structures in obituaries
Issue Date: 2019
metadata.ubs.publikation.typ: Abschlussarbeit (Bachelor)
metadata.ubs.publikation.seiten: 39
URI: http://elib.uni-stuttgart.de/handle/11682/10488
http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-104889
http://dx.doi.org/10.18419/opus-10471
Abstract: Obituaries are a less common text type in research that contains a lot of information about people, events in history and culture. The information that can be obtained by zoning such obituaries enables new research, e.g., in social studies. Our work focuses on the question if the structuring of obituaries is possible and viable. Therefore we created a corpus for this work containing 20058 obituaries of which 1008 were annotated manually by us. We implemented four models, a CNN text classifier and three variations of a Bi-LSTM sequence labeler, to see if the zoning procedure is possible and which among the models performs best for this task. The CNN text classifier showed the most promising results together with the variant of the Bi-LSTM model using a Bag-of-Word model.
Appears in Collections:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Files in This Item:
File Description SizeFormat 
thesis_valentino_sabbatino.pdf681,72 kBAdobe PDFView/Open


Items in OPUS are protected by copyright, with all rights reserved, unless otherwise indicated.