@inproceedings{aramaki-etal-2005-probabilistic,
    title = "Probabilistic Model for Example-based Machine Translation",
    author = "Aramaki, Eiji  and
      Kurohashi, Sadao  and
      Kashioka, Hideki  and
      Kato, Naoto",
    booktitle = "Proceedings of Machine Translation Summit X: Papers",
    month = sep # " 13-15",
    year = "2005",
    address = "Phuket, Thailand",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2005.mtsummit-papers.29/",
    pages = "219--226",
    abstract = "Example-based machine translation (EBMT) systems, so far, rely on heuristic measures in retrieving translation examples. Such a heuristic measure costs time to adjust, and might make its algorithm unclear. This paper presents a probabilistic model for EBMT. Under the proposed model, the system searches the translation example combination which has the highest probability. The proposed model clearly formalizes EBMT process. In addition, the model can naturally incorporate the context similarity of translation examples. The experimental results demonstrate that the proposed model has a slightly better translation quality than state-of-the-art EBMT systems."
}