Incremental Natural Language Processing: Challenges, Strategies, and Evaluation

Arne Köhn


Abstract
Incrementality is ubiquitous in human-human interaction and beneficial for human-computer interaction. It has been a topic of research in different parts of the NLP community, mostly with focus on the specific topic at hand even though incremental systems have to deal with similar challenges regardless of domain. In this survey, I consolidate and categorize the approaches, identifying similarities and differences in the computation and data, and show trade-offs that have to be considered. A focus lies on evaluating incremental systems because the standard metrics often fail to capture the incremental properties of a system and coming up with a suitable evaluation scheme is non-trivial.
Anthology ID:
C18-1253
Volume:
Proceedings of the 27th International Conference on Computational Linguistics
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Editors:
Emily M. Bender, Leon Derczynski, Pierre Isabelle
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2990–3003
Language:
URL:
https://aclanthology.org/C18-1253
DOI:
Bibkey:
Cite (ACL):
Arne Köhn. 2018. Incremental Natural Language Processing: Challenges, Strategies, and Evaluation. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2990–3003, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Incremental Natural Language Processing: Challenges, Strategies, and Evaluation (Köhn, COLING 2018)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/C18-1253.pdf