@inproceedings{plank-2017-1,
    title = "All-In-1 at {IJCNLP}-2017 Task 4: Short Text Classification with One Model for All Languages",
    author = "Plank, Barbara",
    editor = "Liu, Chao-Hong  and
      Nakov, Preslav  and
      Xue, Nianwen",
    booktitle = "Proceedings of the {IJCNLP} 2017, Shared Tasks",
    month = dec,
    year = "2017",
    address = "Taipei, Taiwan",
    publisher = "Asian Federation of Natural Language Processing",
    url = "https://preview.aclanthology.org/fix-sig-urls/I17-4024/",
    pages = "143--148",
    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."
}