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Classification-Based Extension of Wordnets from Heterogeneous Resources

机译:基于分类的异构资源词网扩展

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This paper presents an automatic and language-independent approach for word net extension by reusing existing freely available bilingual resources, such as machine-readable dictionaries and on-line encyclopaedias. The approach is applied to Slovene and French. The words from the bilingual resources are assigned one or several synset ids based on a classifier that relies on a set of features, the most important one of which is distributional similarity. Automatic, manual and task-based evaluations show good results in terms of both coverage and quality.
机译:本文通过重用现有的免费双语资源(例如机器可读词典和在线百科全书),提出了一种自动且独立于语言的词网扩展方法。该方法适用于斯洛文尼亚语和法语。基于依赖于一组功能的分类器,为来自双语资源的单词分配一个或多个同义词集id,其中最重要的一个是分布相似性。自动,手动和基于任务的评估在覆盖率和质量方面均显示出良好的结果。

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