Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality
<|reference_start|>Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality: This paper describes experiments carried out using a variety of machine-learning methods, including the k-nearest neighborhood method that was used in a previous study, for the translation of tense, aspect, and modality. It was found that the support-vector machine method was the most precise of all the methods tested.<|reference_end|>
@article{murata2001using,
    title={Using a Support-Vector Machine for Japanese-to-English Translation of
  Tense, Aspect, and Modality},
    author={Masaki Murata, Kiyotaka Uchimoto, Qing Ma, and Hitoshi Isahara},
    journal={ACL Workshop, the Data-Driven Machine Translation, 2001},
    year={2001},
    archivePrefix={arXiv},
    eprint={cs/0112003},
    primaryClass={cs.CL}
}