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2015

Inverted indexing for cross-lingual NLP

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Inverted indexing for cross-lingual NLP
We present a novel, count-based approach to obtaining inter-lingual word representations based on inverted indexing of Wikipedia. We present experiments applying these representations to 17 datasets in document classification, POS tagging, dependency parsing, and word alignment. Our approach has the advantage that it is simple, computationally efficient and almost parameter-free, and, more importantly, it enables multi-source crosslingual learning. In 14/17 cases, we improve over using state-of-the-art bilingual embeddings.
Anders Søgaard, Zeljko Agic, Héctor
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACL
Authors Anders Søgaard, Zeljko Agic, Héctor Martínez Alonso, Barbara Plank, Bernd Bohnet, Anders Johannsen
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