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@inproceedings{1075316,
author = {Sojka, Petr},
address = {Brno},
booktitle = {Sixth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2012},
edition = {první},
editor = {Aleš Horák, Pavel Rychlý},
keywords = {competing patterns;segmentation;hyphenation;NP problems;pattern generation;patgen;context-sensitive patterns;machine learning;natural language engineering;EuDML},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno},
isbn = {978-80-263-0313-8},
pages = {121--131},
publisher = {Tribun EU},
title = {Segmentation from 97% to 100%: Is It Time for Some Linguistics?},
url = {http://www.fi.muni.cz/usr/sojka/presentations/sojka-raslan-pres2012.pdf},
year = {2012}
}
TY - JOUR
ID - 1075316
AU - Sojka, Petr
PY - 2012
TI - Segmentation from 97% to 100%: Is It Time for Some Linguistics?
PB - Tribun EU
CY - Brno
SN - 9788026303138
KW - competing patterns;segmentation;hyphenation;NP problems;pattern generation;patgen;context-sensitive patterns;machine learning;natural language engineering;EuDML
UR - http://www.fi.muni.cz/usr/sojka/presentations/sojka-raslan-pres2012.pdf
L2 - http://www.fi.muni.cz/usr/sojka/papers/sojka-raslan2012.pdf
N2 - Many tasks in natural language processing (NLP) require \emph{segmentation} algorithms: segmentation of paragraph into sentences, segmentation of sentences into words is needed in languages like Chinese or Thai, segmentation of words into syllables (\emph{hyphenation}) or into morphological parts (e.g.\ getting word stem for indexing), and many other tasks (e.g.\ tagging) could be formulated as segmentation problems. We evaluate methodology of using \emph{competing patterns} for these tasks and decide on the complexity of creation of space-optimal (minimal) patterns that completely (100\,\%) implement the segmentation task. We formally define this task and prove that it is in the class of \emph{non-polynomial} optimization problems. However, finding space-efficient competing patterns for real NLP tasks is feasible and gives efficient scalable solutions of segmentation task: segmentation is done in \emph{constant} time with respect to the size of segmented dictionary. Constant time of access to segmentations makes competing patterns attractive data structure for many NLP tasks.
ER -
SOJKA, Petr. Segmentation from 97\%{} to 100\%{}: Is It Time for Some Linguistics?. Online. In Aleš Horák, Pavel Rychlý. \textit{Sixth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2012}. první. Brno: Tribun EU, 2012. s.~121--131. ISBN~978-80-263-0313-8. [citováno 2024-04-24]
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