@inproceedings{liu-etal-2018-sentence,
    title = "Sentence Suggestion of {J}apanese Functional Expressions for {C}hinese-speaking Learners",
    author = "Liu, Jun  and
      Shindo, Hiroyuki  and
      Matsumoto, Yuji",
    editor = "Liu, Fei  and
      Solorio, Thamar",
    booktitle = "Proceedings of {ACL} 2018, System Demonstrations",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/P18-4010/",
    doi = "10.18653/v1/P18-4010",
    pages = "56--61",
    abstract = "We present a computer-assisted learning system, Jastudy, which is particularly designed for Chinese-speaking learners of Japanese as a second language (JSL) to learn Japanese functional expressions with suggestion of appropriate example sentences. The system automatically recognizes Japanese functional expressions using a free Japanese morphological analyzer MeCab, which is retrained on a new Conditional Random Fields (CRF) model. In order to select appropriate example sentences, we apply a pairwise-based machine learning tool, Support Vector Machine for Ranking (SVMrank) to estimate the complexity of the example sentences using Japanese{--}Chinese homographs as an important feature. In addition, we cluster the example sentences that contain Japanese functional expressions with two or more meanings and usages, based on part-of-speech, conjugation forms of verbs and semantic attributes, using the K-means clustering algorithm in Scikit-Learn. Experimental results demonstrate the effectiveness of our approach."
}