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

Aline Villavicencio, Helena de Medeiros Caseli, A. Machado
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引用次数: 4

Abstract

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.
技术领域中多词表达的识别:调查基于统计和对齐的方法
多词表达式(MWEs)是实现更精确的自然语言处理(NLP)系统的绊脚石之一。资源中缺乏对MWEs的覆盖可能会对任务和应用程序的性能产生负面影响,并可能导致信息丢失或通信错误;特别是在MWE频繁出现的技术领域。本文研究了基于关联度量、词性信息和词法对齐信息的技术语料库多词语义识别方法。我们考察了一些因素对其表现的影响,如识别和评估的信息来源。联想法强调的是召回率,而对齐法强调的是准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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