Abstract
This paper discusses the problem of map translation, of servicing spatial entities in multiple languages. Existing work on entity translation harvests translation evidence from text resources, not considering spatial locality in translation. In contrast, we mine geo-tagged sources for multilingual tags to improve recall, and consider spatial properties of tags for translation to improve precision. Our approach empirically improves accuracy from 0.562 to 0.746 using Taiwanese spatial entities.
Cite
CITATION STYLE
Lee, S., Lee, T., & Hwang, S. W. (2014). Map Translation Using Geo-tagged Social Media. In EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference (pp. 59–63). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/e14-4012
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