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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
Les approches précédentes de récupération de questions dans la réponse aux questions basée sur la communauté s'appuient sur des techniques de traduction statistique pour faire correspondre les questions (requêtes) des utilisateurs avec des collections de questions précédemment posées. Cet article présente une méthode simple mais efficace pour calculer la relation entre les mots afin d'améliorer la récupération des questions sur la base des informations de cooccurrence de mots directement extraites des archives de questions et réponses. Les résultats expérimentaux montrent que l'approche proposée surpasse considérablement les approches basées sur la traduction.
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Jung-Tae LEE, Young-In SONG, Hae-Chang RIM, "Computing Word Semantic Relatedness for Question Retrieval in Community Question Answering" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 4, pp. 736-739, April 2009, doi: 10.1587/transinf.E92.D.736.
Abstract: Previous approaches to question retrieval in community-based question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.736/_p
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@ARTICLE{e92-d_4_736,
author={Jung-Tae LEE, Young-In SONG, Hae-Chang RIM, },
journal={IEICE TRANSACTIONS on Information},
title={Computing Word Semantic Relatedness for Question Retrieval in Community Question Answering},
year={2009},
volume={E92-D},
number={4},
pages={736-739},
abstract={Previous approaches to question retrieval in community-based question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.},
keywords={},
doi={10.1587/transinf.E92.D.736},
ISSN={1745-1361},
month={April},}
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TY - JOUR
TI - Computing Word Semantic Relatedness for Question Retrieval in Community Question Answering
T2 - IEICE TRANSACTIONS on Information
SP - 736
EP - 739
AU - Jung-Tae LEE
AU - Young-In SONG
AU - Hae-Chang RIM
PY - 2009
DO - 10.1587/transinf.E92.D.736
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2009
AB - Previous approaches to question retrieval in community-based question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.
ER -