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Dufter, Philipp; Zhao, Mengjie; Schmitt, Martin; Fraser, Alexander and Schütze, Hinrich (July 2018): Embedding Learning Through Multilingual Concept Induction. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Vol. 1. Association for Computational Linguistics. pp. 1520-1530 [PDF, 453kB]


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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