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EBOOK
Author Tambouratzis, George.
Title Machine translation with minimal reliance on parallel resources / George Tambouratzis, Marina Vassiliou, Sokratis Sofianopoulos.
Imprint Cham : Springer, 2017.

LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
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Author Tambouratzis, George.
Series SpringerBriefs in statistics, 2191-544X
SpringerBriefs in statistics.
Subject Machine translating.
Alt Name Vassiliou, Marina.
Sofianopoulos, Sokratis.
LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Author Tambouratzis, George.
Series SpringerBriefs in statistics, 2191-544X
SpringerBriefs in statistics.
Subject Machine translating.
Alt Name Vassiliou, Marina.
Sofianopoulos, Sokratis.
Description 1 online resource.
Bibliography Note Includes bibliographical references.
Contents Preliminaries -- Implementation -- Main translation process -- Assessing PRESEMT -- Expanding the system -- Extensions to the PRESEMT methodology -- Conclusions and future work -- References.
Summary This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.
Note Online resource; title from PDF title page (EBSCO, viewed August 30, 2017).
ISBN 9783319631073 (electronic bk.)
3319631071 (electronic bk.)
9783319631059
3319631055
ISBN/ISSN 10.1007/978-3-319-63107-3
OCLC # 1001270290
Additional Format Printed edition: 9783319631059



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