Comparative Study of Vietnamese Part-of-Speech Tagging Tools

被引：0

作者：

Luyl-Da Quach ^{[1
]}

Dat Do Thanh ^{[1
]}

Duc Chung Tran ^{[2
]}

Hassan, Mohd Fadzil ^{[3
]}

机构：

[1] FPT Univ, Software Engn Dept, Can Tho, Vietnam

[2] FPT Univ, Comp Fundamental Dept, Hanoi, Vietnam

[3] Univ Teknol PETRONAS, Dept Comp & Informat Sci, Seri Iskandar, Perak, Malaysia

来源：

2020 11TH IEEE CONTROL AND SYSTEM GRADUATE RESEARCH COLLOQUIUM (ICSGRC) | 2020年

关键词：

Vietnamese language processing; part-of-speech tagging; Vietnamese; natural language processing;

D O I：

10.1109/icsgrc49013.2020.9232564

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Vietnamese part-of-speech tagging is one of the most fundamental practices in Vietnamese language processing. Unfortunately, no attempt has been made to empirically compare different Vietnamese part-of-speech tagging software. Therefore, in this paper, the authors experiment upon several Vietnamese part-of-speech tagging software such as VnTagger, RDRPOSTagger (Java Version), JvnTextPro, VNCoreNLP in terms of accuracy, consistency and computational time. In addition, the brief descriptions of the models are discussed in detail. The results help researchers comprehend the models' strengths and weaknesses. The tools are tested on 4 different data sets of number of sentences and different word types such as date, number, special characters, connected characters, double words, compound words, proper names, etc ... The results show that the accuracy of the JvnTextPro tool is high and stable with an accuracy of 80.08 to 97.84%, and the RDPRPOSTagger tool has faster processing time and relatively good accuracy from 88.41 to 96.84%.

引用

页码：197 / 202

页数：6

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