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Identification of Multiword Expressions in Technical Domains: Investigating Statistical and Alignment-Based Approaches

机译:识别技术领域的多字大表达:研究统计和基于对准的方法

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Multiword Expressions (MWEs) are one of the stumbling blocks for more precise Natural Language Processing (NLP) systems. The lack of coverage of MWEs in resources can impact negatively on the performance of tasks and applications, and can lead to loss of information or communication errors; especially in technical domains where MWE are frequent. This paper investigates some approaches to the identification of MWEs in technical corpora based on: association measures, part-of-speech and lexical alignment information. We examine the influence of some factors on their performance such as sources of information for identification and evaluation. While the association measures emphasize recall, the alignment method focuses on precision.
机译:多字型表达式(MWE)是更精确的自然语言处理(NLP)系统的绊脚石之一。资源中的MWE覆盖范围可能会对任务和应用的履行产生负面影响,并可能导致信息或沟通错误丢失;特别是在MWE频繁的技术领域中。本文根据以下:关联措施,言论自由和词汇对齐信息,调查了一些技术集团识别MWE的方法。我们研究一些因素对其绩效的影响,例如鉴定和评估信息来源。虽然关联措施强调召回,但对准方法侧重于精度。

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