为多词表达分类选择更有效的特征，提升跨语言适用性
Choosing features for classifying multiword expressions
- 基于已有跨语言研究，筛选对分类最可靠的特征
- 新分类方案在多种语言上表现更稳定
- 适合需要高泛化能力的自然语言处理任务
多词表达（MWEs）种类繁杂，亟需有效分类。设计合理分类的关键在于特征选择。虽然许多特征可预先获取，但其对MWE分类的可靠性不一，直接影响分类结果的计算可用性。本文提出一种改进的分类方法，整合了涵盖多种语言的前期研究成果，旨在提升分类方案在多语言环境下的适应性与实用性。
原文摘要 · Abstract (English)
Multiword expressions (MWEs) are a heterogeneous set with a glaring need for classifications. Designing a satisfactory classification involves choosing features. In the case of MWEs, many features are a priori available. Not all features are equal in terms of how reliably MWEs can be assigned to classes. Accordingly, resulting classifications may be more or less fruitful for computational use. I outline an enhanced classification. In order to increase its suitability for many languages, I use previous works taking into account various languages.
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