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arXiv · 1801.06807

Embedding Learning Through Multilingual Concept Induction

Philipp Dufter·Mengjie Zhao·Martin Schmitt·Alexander Fraser·Hinrich Schütze
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Abstract

We present a new method for estimating vector space representations of words: embedding learning by concept induction. We test this method on a highly parallel corpus and learn semantic representations of words in 1259 different languages in a single common space. An extensive experimental evaluation on crosslingual word similarity and sentiment analysis indicates that concept-based multilingual embedding learning performs better than previous approaches.

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Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander Fraser, Hinrich Schütze. 2018-01-21. Embedding Learning Through Multilingual Concept Induction. https://arxiv.org/abs/1801.06807

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