@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://aclanthology.org/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.",
}
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%0 Conference Proceedings
%T ClassifierGuesser: A Context-based Classifier Prediction System for Chinese Language Learners
%A Peinelt, Nicole
%A Liakata, Maria
%A Hsieh, Shu-Kai
%Y Park, Seong-Bae
%Y Supnithi, Thepchai
%S Proceedings of the IJCNLP 2017, System Demonstrations
%D 2017
%8 November
%I Association for Computational Linguistics
%C Tapei, Taiwan
%F peinelt-etal-2017-classifierguesser
%X 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.
%U https://aclanthology.org/I17-3011
%P 41-44
Markdown (Informal)
[ClassifierGuesser: A Context-based Classifier Prediction System for Chinese Language Learners](https://aclanthology.org/I17-3011) (Peinelt et al., IJCNLP 2017)
ACL