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

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

26 Oct 2017arXiv:1710.09589archive 2025-07-28

Barbara Plank

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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All General Classification Multilingual Word Embeddings Multilingual text classification Text Classification Word Embeddings text-classification

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