Journal of Natural Language Processing
Online ISSN : 2185-8314
Print ISSN : 1340-7619
ISSN-L : 1340-7619
System Paper
Design and Structure of The Juman++ Morphological Analyzer Toolkit
Arseny TolmachevDaisuke KawaharaSadao Kurohashi
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2020 Volume 27 Issue 1 Pages 89-132

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Abstract

An NLP tool is practical when it is fast in addition to having high accuracy. We describe the architecture and the used methods to achieve 250× analysis speed improvement on the Juman++ morphological analyzer together with slight accuracy improvements. This information should be useful for implementors of high-performance NLP and machine-learning based software.

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© 2020 The Association for Natural Language Processing
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