基于语料库的英语农业半科普文章词汇研究

Qiaoli Quan, Yanqing Liu
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引用次数: 0

摘要

在已有研究成果的基础上,本文对英语词汇解释检索技术进行了深入研究,提出了一种基于语料库的英语词汇解释自动检索技术。本文采用自然语言处理领域中文本形式化的基本思想,利用词性、语法和语义标记对英语词汇的解释进行形式化,主要采用词汇和各种标记单独或混合使用的方式对英语词汇进行序列化解释。为了分析用户输入的英语词汇,第一步是对用户输入的自然语言进行分段,然后提取能够表达句子含义的关键词。基于语料库的英语词汇解释领域本体的构建需要一套完善的工程系统方法。为了实现英语词汇解释的自动检索,构建了英语词汇解释自动检索模型。所构建的英语词汇解释自动检索模型包括语法分析子系统和语法分析子模块。通过对比实验,验证了该技术的检索响应时间更短,检索性能得到提高。
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The vocabulary of agriculture semi-popularization articles in English: A corpus-based study
Based on the obtained research results, this paper makes an in-depth study of English vocabulary interpretation retrieval technology, and proposes a corpus based automatic retrieval technology of English vocabulary interpretation. This paper adopts the basic idea of text formalization in the field of natural language processing, uses part of speech, grammar and semantic markers to formalize the interpretation of English vocabulary, and mainly adopts the way of using vocabulary and various markers separately or mixed to serialize the interpretation of English vocabulary. In order to analyze the user input English vocabulary, the first step is to segment the user input natural language, and then extract the key words which can express the meaning of the sentence. The construction of English vocabulary interpretation domain ontology based on corpus needs a set of perfect engineering system method. The automatic retrieval model of English vocabulary interpretation is constructed to realize the automatic retrieval of English vocabulary interpretation. The constructed automatic retrieval model of English vocabulary interpretation includes grammar analysis subsystem and grammar analysis subsystem. Through comparative experiments, it is verified that the retrieval response time of this technology is shorter, and the retrieval performance is improved.  
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