Learning machine translation

The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Goutte, Cyril [mitwirkender]

Format:	E-Book
Sprache:	Englisch

Erschienen:	Cambridge, Massachusetts: MIT Press ; c2009

Schlagwörter:	Machine translating ; Statistical methods

Anmerkung:	Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015
Umfang:	1 PDF (xii, 316 pages) ; illustrations.
Beschreibung:	Mode of access: World Wide Web.

Reihe:	Neural information processing series

Links:	Link aufrufen Link aufrufen
ISBN:	978-0-262-25509-7

Katalog-ID:	1727351304

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Indexfelder

matchkey_str	book:9780262255097:2008----
oclc_num	1196136635
hierarchy_sort_str	c2009
publishDate	2008
allfields	9780262255097 ebook 978-0-262-25509-7 (DE-627)1727351304 (DE-599)KEP055117201 (OCoLC)1196136635 (MITPRESS)6267198 (EBP)055117201 DE-627 ger DE-627 rda eng 418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Cambridge, Massachusetts MIT Press c2009 1 PDF (xii, 316 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neural information processing series Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015 The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Mode of access: World Wide Web. Machine translating ; Statistical methods Goutte, Cyril mitwirkender ctb 9780262072977 Erscheint auch als Druck-Ausgabe 9780262072977 https://ieeexplore.ieee.org/book/6267198 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 418/.020285 22 01 0018 3848477327 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957242827 olr-MIT i z 23-07-21 100 01 3100 4472469944 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011224251 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753773 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267198 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267198 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267198 100 01 3100 https://ieeexplore.ieee.org/book/6267198 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267198 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267198 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267198 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
spelling	9780262255097 ebook 978-0-262-25509-7 (DE-627)1727351304 (DE-599)KEP055117201 (OCoLC)1196136635 (MITPRESS)6267198 (EBP)055117201 DE-627 ger DE-627 rda eng 418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Cambridge, Massachusetts MIT Press c2009 1 PDF (xii, 316 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neural information processing series Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015 The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Mode of access: World Wide Web. Machine translating ; Statistical methods Goutte, Cyril mitwirkender ctb 9780262072977 Erscheint auch als Druck-Ausgabe 9780262072977 https://ieeexplore.ieee.org/book/6267198 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 418/.020285 22 01 0018 3848477327 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957242827 olr-MIT i z 23-07-21 100 01 3100 4472469944 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011224251 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753773 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267198 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267198 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267198 100 01 3100 https://ieeexplore.ieee.org/book/6267198 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267198 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267198 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267198 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfields_unstemmed	9780262255097 ebook 978-0-262-25509-7 (DE-627)1727351304 (DE-599)KEP055117201 (OCoLC)1196136635 (MITPRESS)6267198 (EBP)055117201 DE-627 ger DE-627 rda eng 418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Cambridge, Massachusetts MIT Press c2009 1 PDF (xii, 316 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neural information processing series Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015 The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Mode of access: World Wide Web. Machine translating ; Statistical methods Goutte, Cyril mitwirkender ctb 9780262072977 Erscheint auch als Druck-Ausgabe 9780262072977 https://ieeexplore.ieee.org/book/6267198 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 418/.020285 22 01 0018 3848477327 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957242827 olr-MIT i z 23-07-21 100 01 3100 4472469944 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011224251 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753773 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267198 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267198 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267198 100 01 3100 https://ieeexplore.ieee.org/book/6267198 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267198 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267198 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267198 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfieldsGer	9780262255097 ebook 978-0-262-25509-7 (DE-627)1727351304 (DE-599)KEP055117201 (OCoLC)1196136635 (MITPRESS)6267198 (EBP)055117201 DE-627 ger DE-627 rda eng 418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Cambridge, Massachusetts MIT Press c2009 1 PDF (xii, 316 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neural information processing series Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015 The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Mode of access: World Wide Web. Machine translating ; Statistical methods Goutte, Cyril mitwirkender ctb 9780262072977 Erscheint auch als Druck-Ausgabe 9780262072977 https://ieeexplore.ieee.org/book/6267198 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 418/.020285 22 01 0018 3848477327 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957242827 olr-MIT i z 23-07-21 100 01 3100 4472469944 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011224251 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753773 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267198 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267198 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267198 100 01 3100 https://ieeexplore.ieee.org/book/6267198 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267198 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267198 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267198 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfieldsSound	9780262255097 ebook 978-0-262-25509-7 (DE-627)1727351304 (DE-599)KEP055117201 (OCoLC)1196136635 (MITPRESS)6267198 (EBP)055117201 DE-627 ger DE-627 rda eng 418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Cambridge, Massachusetts MIT Press c2009 1 PDF (xii, 316 pages) illustrations. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Neural information processing series Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015 The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Mode of access: World Wide Web. Machine translating ; Statistical methods Goutte, Cyril mitwirkender ctb 9780262072977 Erscheint auch als Druck-Ausgabe 9780262072977 https://ieeexplore.ieee.org/book/6267198 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 418/.020285 22 01 0018 3848477327 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957242827 olr-MIT i z 23-07-21 100 01 3100 4472469944 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011224251 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753773 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267198 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267198 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267198 100 01 3100 https://ieeexplore.ieee.org/book/6267198 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267198 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267198 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267198 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
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topic_title	418/.020285 22 Learning machine translation [edited by] Cyril Goutte ... [et al.] Machine translating ; Statistical methods
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abstract	The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015
abstractGer	The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015
abstract_unstemmed	The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies--technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesƒus Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada. Includes bibliographical references (p. [277]-306) and index. - Description based on PDF viewed 12/23/2015
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