Machine Translation using Semantic Web Technologies: A Survey
This is an incremental survey for researchers in machine translation and Semantic Web, highlighting current limitations and potential enhancements.
The paper surveys machine translation approaches that use Semantic Web technologies to address lexical and syntactic ambiguity, finding that while these technologies can improve translation quality, their integration is still in early stages.
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.