Nonsymbolic Text Representation

Hinrich Schütze


Abstract
We introduce the first generic text representation model that is completely nonsymbolic, i.e., it does not require the availability of a segmentation or tokenization method that attempts to identify words or other symbolic units in text. This applies to training the parameters of the model on a training corpus as well as to applying it when computing the representation of a new text. We show that our model performs better than prior work on an information extraction and a text denoising task.
Anthology ID:
E17-1074
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
785–796
Language:
URL:
https://aclanthology.org/E17-1074
DOI:
Bibkey:
Cite (ACL):
Hinrich Schütze. 2017. Nonsymbolic Text Representation. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 785–796, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Nonsymbolic Text Representation (Schütze, EACL 2017)
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PDF:
https://preview.aclanthology.org/update-css-js/E17-1074.pdf