Machine translation
Mapping technological developments through scientometrics
DOI:
https://doi.org/10.18225/ci.inf.v51i3.5542Keywords:
Machine Translation. Translation Technologies. Scientometrics.Abstract
Conceived as a scientometric study, this paper searches for comprehending the research status of machine translation on the IEEE database from 1956 to 2019. Documents were analyzed considering a series of measures such as most prominent academic institutions and countries that investigate machine translation, citation, co-authorship, keywords co-occurrence, reference coupling, and textual-based analysis retrieved from the documents’ titles and abstracts. Through VOSviewer software and its tools for data collecting and visualization, machine translation research in the circumscribed database and period of time is focused on three main aspects: machine translation systems, statistical machine translation and English language.
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References
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DOORSLAER, L. V.; GAMBIER, Y. Measuring relationships in Translation Studies. On affiliations and keyword frequencies in the Translation Studies Bibliography. Perspectives: Studies in Translatology, v. 23, n. 2, p. 305-319, 2015. DOI: 10.1080/0907676X.2015.1026360. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/0907676X.2015.1026360?needAccess=true.
Latest access: April 29 2020.
GAO, B; CHAI, M. A bibliometric analysis of new developments in simultaneous interpreting studies in the West. Chinese Translators Journal, v. 2, p. 17-21, 2009.
GARFIELD, E. Validation of citation analysis. Journal of the American Society for Information Science, v. 48, p. 962-964, 1997.
GILE, D. Analyzing Translation studies with scientometric data: from CIRIN to citation analysis. Perspectives: Studies in Translatology, v. 23, n. 2, p. 240–248, 2015. DOI: https://doi.org/10.1080/0907676X.2014.972418. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/0907676X.2014.972418?needAccess=true. Latest access: April 29 2020.
HUTCHINS, W. J. Machine translation: history of research and applications. In: SIN-WAI, C. (ed.). The Routledge encyclopedia of translation technology. London/New York: Routledge, 2015, p. 120-136.
HUTCHINS, W. J. Machine translation: past, present, future. Chichester: Ellis Horwood, 1986.
JIMÉNEZ-CRESPO, M. A. Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies. In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 69-93.
KENNY, D.; DOHERTY, S. Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators. The Interpreter and Translator Trainer, v. 8, n. 2, p. 276-294, 2014. DOI: https://doi.org/10.1080/1750399X.2014.936112. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/1750399X.2014.936112?casa_token=N5ph6XsUy-4AAAAA:QFS5MTPuKHEs3XJprB2bhJr7qq8bFCnUfJc2fZeSqrz4a9mOf4X4Q72Zbm4ow1vNxPQ3uvfqlyDtZGiU. Latest access: April 21 2020.
MACÍAS-CHAPULA, C. A. Papel de la informetría y de la cienciometría y su perspectiva nacional e internacional. Acimed, v. 9, p. 35-41, 2001. Retrieved from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1024-94352001000400006. Latest access: April 29 2020.
MARTINS, R. T.; NUNES, M. G. Noções gerais de tradução automática. Notas didáticas do ICMC – USP, São Carlos, n. 68, p.1-26, 2005. Retrieved from: http://www.nilc.icmc.usp.br/nilc/download/NotasDidaticasICMC_68.pdf. Latest access: April 2 2020.
MELBY, A. K. Future of machine translation: Musings on Weaver’s memo. In: O’HAGAN, M. The Routledge Handbook of Translation and Technology. New York: Routledge, 2020, p. 419-436.
MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018.
OLADOSU, J. et al. Approaches to Machine Translation: A Review. FUOYE Journal of Engineering and Technology, v.1, n.1, p. 120-162. 2016. Retrieved from: http://engineering.fuoye.edu.ng/journal/index.php/engineer/article/view/26/pdf. Latest access: April 20 2020.
OLOHAN, M. Scientific and Technical Translation. London and New York: Routledge, 2016.
OTLET, P. Traité de documentation: le livre sur le livre – théorie et pratique. Bruxelas: Editiones Mundaneum, 1934.
PYM, A. Translation Skill-Sets in a Machine-Translation Age. Meta, v. 58, n. 3, p. 487–503, 2013. DOI: https://doi.org/10.7202/1025047ar. Retrieved from: https://www.erudit.org/en/journals/meta/2013-v58-n3-meta01406/1025047ar.pdf. Latest access: April 1 2020.
SHIWEN, Y; XIAOJING, B. Rule-based machine translation. In: SIN-WAI, C. (ed.). The Routledge encyclopedia of translation technology. London/New York: Routledge, 2015, p. 186-200.
TANG, F. A bibliometric analysis of empirical interpreting studies in China: Based on data of experimental research papers. Foreign Language World, n. 2, p. 39-46, 2010.
THENMOZHI, D.; ARAVINDAN, C. Paraphrase Identification by Using Clause-Based Similarity Features and Machine Translation Metrics. The Computer Journal, v. 59, n. 9, p. 1289-1302, 2015. DOI: https://doi.org/10.1093/comjnl/bxv083.
TORAL, A.; WAY, A. What Level of Quality Can Neural Machine Translation Attain on Literary Text? In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 263-287.
TRANSLATION STUDIES BIBLIOGRAPHY. Amsterdam: John Benjamins Publishing Company. Available at: https://benjamins.com/online/tsb/.
VAN ECK, N. J.; WALTMAN, L. VOSviewer manual. Leiden: Univeristeit Leiden, v. 1, n. 1, 2018. Retrieved from: https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.10.pdf. Latest access: April 29 2020.
VANTI, N. A. P. Da bibliometria à webmetria: uma exploração conceitual dos mecanismos utilizados para medir o registro da informação e a difusão do conhecimento. Ciência da Informação, v. 31, n. 2, p. 152–162, 2002. DOI: http://dx.doi.org/10.1590/S0100-19652002000200016 . Retrieved from: https://www.scielo.br/scielo.php?pid=s0100-19652002000200016&script=sci_arttext&tlng=pt. Latest access: April 20 2020.
VOSS, S.; ZHAO, X. Some steps towards a scientometric analysis of publications in machine translation. IASTED In Conference on Artificial Intelligence and Applications. Innsbruck, Austria: Multi-Conference on Applied Informatics, 2005, p. 651-655.
WANG, B. Describing the progress of interpreting studies in China: A bibliometrical analysis of CSSCI/CORE journal articles during the past five years. Babel, v. 61, n. 1, p. 62-77, 2015.
WANG, B.; MU, L. Interpreter training and research in mainland China: Recent developments. Interpreting: International Journal of Interpreting Theory and Practice, n. 11, p. 267–283, 2009.
WAY, A. Quality Expectations of Machine Translation. In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 159-178.
WILLIAMS, P. et al. Syntax-based statistical machine translation. Synthesis Lectures on Human Language Technologies, v. 9, n. 4, p. 1-208, 2016.
BOWKER, L. Fit-for-purpose translation. In: O’HAGAN, M. The Routledge Handbook of Translation and Technology. New York: Routledge, 2020, p. 319-335.
BOWKER, L.; BUITRAGO CIRO, J. Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community. United Kingdom: Emerald Publishing Limited, 2019.
DOHERTY, S. et al. On Education and Training in Translation Quality Assessment. In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 95-106.
FRANCO AIXELÁ, Javier. 2001-2020. BITRA (Bibliography of Interpreting and Translation). Open-access database. DOI: 10.14198/bitra. Available at: http://dti.ua.es/en/bitra/introduction.html.
GUPTA, B. M.; DHAWAN, S. M. Machine Translation Research: A Scientometric Assessment of Global Publications Output during 2007-16. DESIDOC Journal of Library & Information Technology, v. 39, n. 1, p. 31-38, 2019. DOI: 10.14429/djlit.39.1.13558. Retrieved from: https://www.researchgate.net/profile/Brij_Mohan_Gupta/publication/331326073_Machine_Translation_Research_A_Scientometric_Assessment_of_Global_Publications_Output_during_2007_16/links/5dd79fce92851c1feda58cc8/Machine-Translation-Research-A-Scientometric-Assessment-of-Global-Publications-Output-during-2007-16.pdf. Latest Access: April 20 2020.
DONG, D.; CHEN, M.-L. Publication trends and co-citation mapping of translation studies between 2000 and 2015. Scientometrics, v. 105, n. 2, p. 1111-1128, 2015. DOI: https://doi.org/10.1007/s11192-015-1769-1. Retrieved from: https://link.springer.com/content/pdf/10.1007/s11192-015-1769-1.pdf. Latest access: April 29 2020.
DOORSLAER, L. V.; GAMBIER, Y. Measuring relationships in Translation Studies. On affiliations and keyword frequencies in the Translation Studies Bibliography. Perspectives: Studies in Translatology, v. 23, n. 2, p. 305-319, 2015. DOI: 10.1080/0907676X.2015.1026360. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/0907676X.2015.1026360?needAccess=true.
Latest access: April 29 2020.
GAO, B; CHAI, M. A bibliometric analysis of new developments in simultaneous interpreting studies in the West. Chinese Translators Journal, v. 2, p. 17-21, 2009.
GARFIELD, E. Validation of citation analysis. Journal of the American Society for Information Science, v. 48, p. 962-964, 1997.
GILE, D. Analyzing Translation studies with scientometric data: from CIRIN to citation analysis. Perspectives: Studies in Translatology, v. 23, n. 2, p. 240–248, 2015. DOI: https://doi.org/10.1080/0907676X.2014.972418. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/0907676X.2014.972418?needAccess=true. Latest access: April 29 2020.
HUTCHINS, W. J. Machine translation: history of research and applications. In: SIN-WAI, C. (ed.). The Routledge encyclopedia of translation technology. London/New York: Routledge, 2015, p. 120-136.
HUTCHINS, W. J. Machine translation: past, present, future. Chichester: Ellis Horwood, 1986.
JIMÉNEZ-CRESPO, M. A. Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies. In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 69-93.
KENNY, D.; DOHERTY, S. Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators. The Interpreter and Translator Trainer, v. 8, n. 2, p. 276-294, 2014. DOI: https://doi.org/10.1080/1750399X.2014.936112. Retrieved from: https://www.tandfonline.com/doi/pdf/10.1080/1750399X.2014.936112?casa_token=N5ph6XsUy-4AAAAA:QFS5MTPuKHEs3XJprB2bhJr7qq8bFCnUfJc2fZeSqrz4a9mOf4X4Q72Zbm4ow1vNxPQ3uvfqlyDtZGiU. Latest access: April 21 2020.
MACÍAS-CHAPULA, C. A. Papel de la informetría y de la cienciometría y su perspectiva nacional e internacional. Acimed, v. 9, p. 35-41, 2001. Retrieved from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1024-94352001000400006. Latest access: April 29 2020.
MARTINS, R. T.; NUNES, M. G. Noções gerais de tradução automática. Notas didáticas do ICMC – USP, São Carlos, n. 68, p.1-26, 2005. Retrieved from: http://www.nilc.icmc.usp.br/nilc/download/NotasDidaticasICMC_68.pdf. Latest access: April 2 2020.
MELBY, A. K. Future of machine translation: Musings on Weaver’s memo. In: O’HAGAN, M. The Routledge Handbook of Translation and Technology. New York: Routledge, 2020, p. 419-436.
MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018.
OLADOSU, J. et al. Approaches to Machine Translation: A Review. FUOYE Journal of Engineering and Technology, v.1, n.1, p. 120-162. 2016. Retrieved from: http://engineering.fuoye.edu.ng/journal/index.php/engineer/article/view/26/pdf. Latest access: April 20 2020.
OLOHAN, M. Scientific and Technical Translation. London and New York: Routledge, 2016.
OTLET, P. Traité de documentation: le livre sur le livre – théorie et pratique. Bruxelas: Editiones Mundaneum, 1934.
PYM, A. Translation Skill-Sets in a Machine-Translation Age. Meta, v. 58, n. 3, p. 487–503, 2013. DOI: https://doi.org/10.7202/1025047ar. Retrieved from: https://www.erudit.org/en/journals/meta/2013-v58-n3-meta01406/1025047ar.pdf. Latest access: April 1 2020.
SHIWEN, Y; XIAOJING, B. Rule-based machine translation. In: SIN-WAI, C. (ed.). The Routledge encyclopedia of translation technology. London/New York: Routledge, 2015, p. 186-200.
TANG, F. A bibliometric analysis of empirical interpreting studies in China: Based on data of experimental research papers. Foreign Language World, n. 2, p. 39-46, 2010.
THENMOZHI, D.; ARAVINDAN, C. Paraphrase Identification by Using Clause-Based Similarity Features and Machine Translation Metrics. The Computer Journal, v. 59, n. 9, p. 1289-1302, 2015. DOI: https://doi.org/10.1093/comjnl/bxv083.
TORAL, A.; WAY, A. What Level of Quality Can Neural Machine Translation Attain on Literary Text? In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 263-287.
TRANSLATION STUDIES BIBLIOGRAPHY. Amsterdam: John Benjamins Publishing Company. Available at: https://benjamins.com/online/tsb/.
VAN ECK, N. J.; WALTMAN, L. VOSviewer manual. Leiden: Univeristeit Leiden, v. 1, n. 1, 2018. Retrieved from: https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.10.pdf. Latest access: April 29 2020.
VANTI, N. A. P. Da bibliometria à webmetria: uma exploração conceitual dos mecanismos utilizados para medir o registro da informação e a difusão do conhecimento. Ciência da Informação, v. 31, n. 2, p. 152–162, 2002. DOI: http://dx.doi.org/10.1590/S0100-19652002000200016 . Retrieved from: https://www.scielo.br/scielo.php?pid=s0100-19652002000200016&script=sci_arttext&tlng=pt. Latest access: April 20 2020.
VOSS, S.; ZHAO, X. Some steps towards a scientometric analysis of publications in machine translation. IASTED In Conference on Artificial Intelligence and Applications. Innsbruck, Austria: Multi-Conference on Applied Informatics, 2005, p. 651-655.
WANG, B. Describing the progress of interpreting studies in China: A bibliometrical analysis of CSSCI/CORE journal articles during the past five years. Babel, v. 61, n. 1, p. 62-77, 2015.
WANG, B.; MU, L. Interpreter training and research in mainland China: Recent developments. Interpreting: International Journal of Interpreting Theory and Practice, n. 11, p. 267–283, 2009.
WAY, A. Quality Expectations of Machine Translation. In: MOORKENS, J.; CASTILHO, S; GASPARI, F; DOHERTY, S. (eds.). Translation Quality Assessment: From Principles to Practice. Machine Translation Series. Switzerland: Springer International Publishing, 2018, p. 159-178.
WILLIAMS, P. et al. Syntax-based statistical machine translation. Synthesis Lectures on Human Language Technologies, v. 9, n. 4, p. 1-208, 2016.
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