基于语料库的泰语词汇表

Pub Date : 2023-01-01 DOI:10.12720/jait.14.2.319-327
H. Ketmaneechairat, Maleerat Maliyaem
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引用次数: 1

摘要

-对于自然语言处理,语料库对于训练模型和创建机器学习模型的算法都很重要。本文旨在描述一个基于语料库的泰语词汇库的设计和创建过程,该语料库可作为自然语言处理研究的主要语料库。语料库是在语言的调节下产生的。通过使用实际的词使用频率(WUF)分析从文本语料库中涵盖的几种类型的内容。结果显示了几个特征的使用频率,即词语使用频率、字符使用频率和双字使用频率。用于本研究,并作为进一步NLP研究的重要信息。基于这些发现,我们得出结论,当语料库中的单词数量增加时,平均单词长度也会增加。这意味着单词长度和单词频率之间的相关性是相同的方向。
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Corpus-Based Vocabulary List for Thai Language
—For natural language processing, a corpus is important for training models as also for the algorithms to create the machine learning models. This paper aimed to describe the design and process in creating a corpus-based vocabulary in the Thai language that can be used as a main corpus for natural language processing research. A corpus is created under the regulation of language. By using the actual Word Usage Frequency (WUF) analyzed from a text corpus cover several types of contents. The results presented the frequency of use of several characteristics, namely the frequency of word use character usage frequency and the frequency of using bigram characters. To be used in this research and used as important information for further NLP research. Based on the findings, it was concluded that the average word length increases when the number of words in the corpus increases. It means that the correlation between word length and frequency of words is in the same direction.
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