计算语言学中的手工特征

Bruce W. Lee, J. Lee
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引用次数: 3

摘要

过去的研究已经确定了一套丰富的手工语言特征,可以潜在地帮助各种任务。然而,它们的大量数量使得有效地选择和利用现有的手工特征变得困难。再加上研究工作之间实现不一致的问题,目前还没有一个分类方案或普遍接受的特征名称。这会造成不必要的混乱。此外,没有一个主动维护的开源库能够提取大量手工制作的特性。目前的手工特征提取方法有几个效率低下的地方,研究人员经常不得不从头开始构建这样一个提取系统。我们收集和分类超过220个流行的手工特征,以过去的文学为基础。然后,我们对几个特定于任务的数据集进行相关性分析研究,并报告每个特征的潜在用例。最后,我们设计了一个可系统扩展的多语种手工语言特征提取系统。我们开源了我们的系统,为社区提供了一套丰富的预先实现的手工功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
LFTK: Handcrafted Features in Computational Linguistics
Past research has identified a rich set of handcrafted linguistic features that can potentially assist various tasks. However, their extensive number makes it difficult to effectively select and utilize existing handcrafted features. Coupled with the problem of inconsistent implementation across research works, there has been no categorization scheme or generally-accepted feature names. This creates unwanted confusion. Also, no actively-maintained open-source library extracts a wide variety of handcrafted features. The current handcrafted feature extraction practices have several inefficiencies, and a researcher often has to build such an extraction system from the ground up. We collect and categorize more than 220 popular handcrafted features grounded on past literature. Then, we conduct a correlation analysis study on several task-specific datasets and report the potential use cases of each feature. Lastly, we devise a multilingual handcrafted linguistic feature extraction system in a systematically expandable manner. We open-source our system to give the community a rich set of pre-implemented handcrafted features.
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