The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L’extraction de synonymes de verbes est une technologie clé pour créer un dictionnaire de verbes en tant que ressource linguistique. Cet article présente une approche d'extraction de synonymes de verbes basée sur le co-clustering qui augmente le nombre de significations extraites de verbes polysémiques à partir d'un grand corpus de texte. Pour l'extraction de synonymes de verbes avec une approche de regroupement traitant des verbes polysémiques, cela peut poser problème car chaque verbe polysémique doit être classé en différents groupes en fonction de chaque signification ; il existe donc une forte possibilité de ne pas réussir à extraire certaines significations des verbes polysémiques. L'approche proposée permet d'extraire les différentes significations des verbes polysémiques en éliminant récursivement les clusters extraits de l'ensemble de données initial. Les résultats expérimentaux de l'extraction des synonymes de verbe montrent que l'approche proposée augmente les groupes de verbes corrects d'environ 50 % avec une augmentation de 0.9 % en précision et une augmentation de 1.5 % en rappel par rapport à l'approche précédente.
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Koichi TAKEUCHI, Hideyuki TAKAHASHI, "Co-clustering with Recursive Elimination for Verb Synonym Extraction from Large Text Corpus" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 12, pp. 2334-2340, December 2009, doi: 10.1587/transinf.E92.D.2334.
Abstract: The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a co-clustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meaning; thus there is a high possibility of failing to extract some of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.2334/_p
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@ARTICLE{e92-d_12_2334,
author={Koichi TAKEUCHI, Hideyuki TAKAHASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Co-clustering with Recursive Elimination for Verb Synonym Extraction from Large Text Corpus},
year={2009},
volume={E92-D},
number={12},
pages={2334-2340},
abstract={The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a co-clustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meaning; thus there is a high possibility of failing to extract some of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.},
keywords={},
doi={10.1587/transinf.E92.D.2334},
ISSN={1745-1361},
month={December},}
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TY - JOUR
TI - Co-clustering with Recursive Elimination for Verb Synonym Extraction from Large Text Corpus
T2 - IEICE TRANSACTIONS on Information
SP - 2334
EP - 2340
AU - Koichi TAKEUCHI
AU - Hideyuki TAKAHASHI
PY - 2009
DO - 10.1587/transinf.E92.D.2334
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2009
AB - The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a co-clustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meaning; thus there is a high possibility of failing to extract some of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.
ER -