@inproceedings{peinelt-etal-2017-classifierguesser,
    title = "{C}lassifier{G}uesser: A Context-based Classifier Prediction System for {C}hinese Language Learners",
    author = "Peinelt, Nicole  and
      Liakata, Maria  and
      Hsieh, Shu-Kai",
    editor = "Park, Seong-Bae  and
      Supnithi, Thepchai",
    booktitle = "Proceedings of the {IJCNLP} 2017, System Demonstrations",
    month = nov,
    year = "2017",
    address = "Tapei, Taiwan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/I17-3011/",
    pages = "41--44",
    abstract = "Classifiers are function words that are used to express quantities in Chinese and are especially difficult for language learners. In contrast to previous studies, we argue that the choice of classifiers is highly contextual and train context-aware machine learning models based on a novel publicly available dataset, outperforming previous baselines. We further present use cases for our database and models in an interactive demo system."
}