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arXiv · 1710.09589

ALL-IN-1: Short Text Classification with One Model for All Languages

Barbara Plank
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Abstract

We present ALL-IN-1, a simple model for multilingual text classification that does not require any parallel data. It is based on a traditional Support Vector Machine classifier exploiting multilingual word embeddings and character n-grams. Our model is simple, easily extendable yet very effective, overall ranking 1st (out of 12 teams) in the IJCNLP 2017 shared task on customer feedback analysis in four languages: English, French, Japanese and Spanish.

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Barbara Plank. 2017-10-26. ALL-IN-1: Short Text Classification with One Model for All Languages. https://arxiv.org/abs/1710.09589

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