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Domain Adaptation by Active Learning

机译:通过主动学习的域适应

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摘要

We tackled the Evalita 2011 Domain Adaptation task with a strategy of active learning. The DeSR parser can be configured to provide different measures of perplexity in its own ability to parse sentences correctly. After parsing sentences in the target domain, a small number of the sentences with the highest perplexity were selected, revised manually and added to the training corpus in order to build a new parser model incorporating some knowledge from the target domain. The process was repeated a few times for building a new training resource partially adapted to the target domain. Using the new resource we trained three stacked parsers, and their combination was used to produce the final results.
机译:我们通过主动学习策略解决了评估2011年域适应任务。 DESR解析器可以配置为提供不同的困惑测量,以其正确的解析句子的能力。在解析目标域中的句子之后,选择少量具有最高困惑的句子,手动修改并添加到培训语料库中,以构建包含来自目标域的一些知识的新解析器模型。该过程重复几次,用于构建部分适用于目标域的新培训资源。使用新资源我们培训了三个堆叠的解析器,它们的组合用于产生最终结果。

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