Map Translation Using Geo-tagged Social Media

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.