经验主义时期国际机器翻译演化路径及前沿探析

The Evolution Path and Frontier Analysis of International Machine Translation in the Period of Empiricism

With the advent of the age of big data, machine translation has been receiving more and more attention as an important branch of artificial intelligence. The bibliometric study of international machine translation can help domestic scholars to better grasp the development of machine translation and find out the inadequacies of current machine translation research. This paper uses CiteSpace V as a tool to systematically analyze the status, hotspots and frontier trends of research in international machine translation from 1993 to 2017 by using the map of dual-map overlays of journal, the cooperation maps of authors-institutions-country, and the clustering map of the co-citation literatures. In the field of international machine translation, chronological order of the hotspots is machine translation based on statistical principle only, statistical machine translation using linguistic information, domain adaptation, neural machine translation, research frontier includes translation of low-resource language, post-editing, quality estimation of machine translation. This paper holds that the field of machine translation at the moment needs further strengthening in the development of the application of the existing machine translation technology, the fusion of cognitive linguistics and machine translation technology.

随着大数据时代的到来，机器翻译作为人工智能领域的一个重要分支正在受到越来越多的关注。对国际机器翻译进行文献计量研究有助于学者更好地把握机器翻译的发展动态，发现当前机器翻译研究的不足之处。本研究以CiteSpace V为工具，运用期刊双图叠加图谱、作者-机构-国家合作图谱、文献共被引聚类图谱系统地分析了1993-2017年经验主义时期间国际机器翻译领域的研究状况、热点主题以及前沿趋势等问题。经研究发现国际机器翻译领域的热点依次为仅依靠统计学原理的机器翻译、综合运用语言学信息的统计机器翻译、领域自适应、神经机器翻译，研究前沿为低资源语言的翻译、译后编辑、质量评估标准。最后，当前国际机器翻译领域在既有机器翻译技术应用模式的开发、认知语言学等先验知识与机器翻译技术的融合两个方面有待进一步加强。