Learning Reliable Information for Dependency Parsing Adaptation

  title={Learning Reliable Information for Dependency Parsing Adaptation},
  author={Wenliang Chen and Youzheng Wu and Hitoshi Isahara},
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn reliable information from unlabeled target domain data for dependency parsing adaptation. Current state-of-the-art statistical parsers perform much better for shorter dependencies than for longer ones. Thus we propose an adaptation approach by learning reliable information on shorter dependencies in an unlabeled target data… CONTINUE READING
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