Anaphora Resolution in Arabic/English Machine Translation Systems: A Statistical, Knowledge-Poor Approach to Arabic Pronominal Anaphora Resolution - Couverture souple

Al-Sabbagh, Rania

 
9783838386843: Anaphora Resolution in Arabic/English Machine Translation Systems: A Statistical, Knowledge-Poor Approach to Arabic Pronominal Anaphora Resolution
Couverture souple
ISBN 10 : 3838386841 ISBN 13 : 9783838386843
Editeur : LAP LAMBERT Academic Publishing, 2010

Synopsis

Anaphora Resolution (AR) is the process of determining the antecedent of a given anaphor. The present book focuses on pronominal AR in Modern Standard Arabic (MSA) which is a crucially required task for many Natural Language Processing (NLP) applications, including but not limited to Machine Translation (MT). Current MT systems poorly handle anaphora resolution when working on Arabic-English translation or vice versa, given that anaphora resolution is one of the least studied issues in Arabic NLP due to the fact that AR requires many NLP morphological, semantic and syntactic tools and resources; many of which are not available for MSA. Motivated by the poor performance of current MT systems in terms of Arabic AR and the lack of sufficient NLP research on the issue, this book proposes a statistical, corpus-based approach to AR in MSA that successfully overcomes the major bottleneck of Arabic NLP, namely the lack of basic language processing tools and resources. Such an approach achieves a promising performance rate of 87.6% and sheds light on further future work which can significantly improve performance.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Anaphora Resolution (AR) is the process of determining the antecedent of a given anaphor. The present book focuses on pronominal AR in Modern Standard Arabic (MSA) which is a crucially required task for many Natural Language Processing (NLP) applications, including but not limited to Machine Translation (MT). Current MT systems poorly handle anaphora resolution when working on Arabic-English translation or vice versa, given that anaphora resolution is one of the least studied issues in Arabic NLP due to the fact that AR requires many NLP morphological, semantic and syntactic tools and resources; many of which are not available for MSA. Motivated by the poor performance of current MT systems in terms of Arabic AR and the lack of sufficient NLP research on the issue, this book proposes a statistical, corpus-based approach to AR in MSA that successfully overcomes the major bottleneck of Arabic NLP, namely the lack of basic language processing tools and resources. Such an approach achieves a promising performance rate of 87.6% and sheds light on further future work which can significantly improve performance.

Biographie de l'auteur

Rania Al-Sabbagh is a PhD student at the Department of Linguistics, University of Illinois at Urbana-Champaign (UIUC). She is a winner of the Artificial Intelligence/Cognitive Science Award for 2010, the Beckman Institute, UIUC. Her research interests include computational semantics, pragmatics and discourse analysis for Arabic and its dialects.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
3838386841
ISBN 13 
9783838386843
Reliure
Broché
Nombre de pages
104
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne