Machine Translation using Semantic Web Technologies: A Survey

November 26, 2017 ยท The Cartographer ยท ๐Ÿ› Journal of Web Semantics

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Machine Translation using Semantic Web Technologies: A Survey"

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Authors Diego Moussallem, Matthias Wauer, Axel-Cyrille Ngonga Ngomo arXiv ID 1711.09476 Category cs.CL: Computation & Language Citations 64 Venue Journal of Web Semantics Last Checked 1 day ago
Abstract
A large number of machine translation approaches have recently been developed to facilitate the fluid migration of content across languages. However, the literature suggests that many obstacles must still be dealt with to achieve better automatic translations. One of these obstacles is lexical and syntactic ambiguity. A promising way of overcoming this problem is using Semantic Web technologies. This article presents the results of a systematic review of machine translation approaches that rely on Semantic Web technologies for translating texts. Overall, our survey suggests that while Semantic Web technologies can enhance the quality of machine translation outputs for various problems, the combination of both is still in its infancy.
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