整合基于语料库和自然语言处理的方法提取术语和面向领域的信息:以美国军事语料库为例

IF 0.6 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Acta Scientiarum-technology Pub Date : 2022-07-28 DOI:10.4025/actascitechnol.v44i1.60486
Liang-Ching Chen, Kuei-Hu Chang, Shu-Ching Yang
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引用次数: 1

摘要

在现代信息、通信和技术(ICT)中,寻求高效、准确的基于语料库的方法来处理自然语言数据(NLD)至关重要。传统的基于语料库的语料库(即收集到的NLD)处理方法主要集中在对词进行量化和排序,以帮助人类提取关键词。然而,传统的基于语料库的方法无法识别单词背后的含义,从而无法正确提取术语及其信息。为了解决这一问题,本文的主要目标是提出一种集成的语言分析方法,该方法结合了两种基于语料库的方法和基于规则的自然语言处理(NLP)方法来提取和识别术语,并创建文本数据库,通过将术语作为从目标语料库中检索核心信息的通道来提取更深层次的面向领域的信息。军事领域是一个不常见的研究领域,经常被列为机密数据,因此研究很少受到关注。然而,军事情报对国家安全至关重要,不应被忽视。因此,为了验证所提出的方法在提取术语和术语信息方面的有效性,研究人员采用美国陆军野战手册(FM) 8-10-6作为目标语料库和经验案例。与AntConc 3.5.8和Tongpoon-Patanasorn的混合方法相比,结果表明,从术语识别、文本数据库创建、领域知识提取等方面来看,只有本文提出的方法才能解决所有这些问题。
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Integrating corpus-based and NLP approach to extract terminology and domain-oriented information: an example of US military corpus
Within the modern information, communication and technology (ICT), seeking high efficient and accurate corpus-based approaches to process natural language data (NLD) is critical. Traditional corpus-based approaches for processing corpus (i.e. the collected NLD) mainly focused on quantifying and ranking words for assisting human in extracting keywords. However, traditional corpus-based approaches cannot identify the meanings behind the words to properly extract terminologies nor their information. To address this issue, the main objective of this paper is to propose an integrated linguistic analysis approach that combines two corpus-based approaches and a rule-based natural language processing (NLP) approach to extract and identify terminologies and create the text database for extracting deeper domain-oriented information by using the terminologies as channels to retrieve core information from the target corpus. Military domain is an uncommon research field and often classified as confidential data, which caused little researches to focus on. Nevertheless, military information is vital to national security and should not be ignored. Hence, to verify the proposed approach in extracting terminologies and information of the terminologies, the researchers adopt the US Army field manual (FM) 8-10-6 as the target corpus and empirical case. Compared with AntConc 3.5.8 and Tongpoon-Patanasorn’s hybrid approach, the results indicate that from the perspectives of terminology identification, texts database creation, domain knowledge extraction, only the proposed approach can handle all these issues.
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来源期刊
Acta Scientiarum-technology
Acta Scientiarum-technology 综合性期刊-综合性期刊
CiteScore
1.40
自引率
12.50%
发文量
60
审稿时长
6-12 weeks
期刊介绍: The journal publishes original articles in all areas of Technology, including: Engineerings, Physics, Chemistry, Mathematics, Statistics, Geosciences and Computation Sciences. To establish the public inscription of knowledge and its preservation; To publish results of research comprising ideas and new scientific suggestions; To publicize worldwide information and knowledge produced by the scientific community; To speech the process of scientific communication in Technology.
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