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- W2766285488 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." @default.
- W2766285488 created "2017-11-10" @default.
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- W2766285488 date "2017-10-26" @default.
- W2766285488 modified "2023-09-27" @default.
- W2766285488 title "ALL-IN-1: Short Text Classification with One Model for All Languages." @default.
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