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Incorporating Subword Information into Matrix Factorization Word Embeddings

2018-05-09WS 2018Code Available0· sign in to hype

Alexandre Salle, Aline Villavicencio

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Abstract

The positive effect of adding subword information to word embeddings has been demonstrated for predictive models. In this paper we investigate whether similar benefits can also be derived from incorporating subwords into counting models. We evaluate the impact of different types of subwords (n-grams and unsupervised morphemes), with results confirming the importance of subword information in learning representations of rare and out-of-vocabulary words.

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