Matrix and Double-Array Representations for Efficient Finite State Tokenization

Nils Diewald


Abstract
This paper presents an algorithm and implementation for efficient tokenization of space-delimited languages based on a deterministic finite state automaton. Two representations of the underlying data structure are presented and a model implementation for German is compared with state-of-the-art approaches. The presented solution is faster than other tools while maintaining comparable quality.
Anthology ID:
2022.cmlc-1.4
Volume:
Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-10)
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Piotr Banski, Adrien Barbaresi, Simon Clematide, Marc Kupietz, Harald Lüngen
Venue:
CMLC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
20–26
Language:
URL:
https://aclanthology.org/2022.cmlc-1.4
DOI:
Bibkey:
Cite (ACL):
Nils Diewald. 2022. Matrix and Double-Array Representations for Efficient Finite State Tokenization. In Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-10), pages 20–26, Marseille, France. European Language Resources Association.
Cite (Informal):
Matrix and Double-Array Representations for Efficient Finite State Tokenization (Diewald, CMLC 2022)
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PDF:
https://aclanthology.org/2022.cmlc-1.4.pdf