计算机与数字工程2025，Vol.53Issue(5)：1226-1229,1268,5.DOI:10.3969/j.issn.1672-9722.2025.05.003
基于双层隐马尔可夫模型的英文词性标注研究
Research on English Part-of-speech Tagging Based on Double-Layer Hidden Markov Model
赖威 1金忠1
作者信息
- 1. 南京理工大学计算机科学与工程学院 南京 210094||南京理工大学高维信息智能感知与系统教育部重点实验室 南京 210094
- 折叠
摘要
Abstract
Based on the traditional first-order hidden Markov model,this paper proposes a double-layer hidden Markov mod-el to solve the problem of incomplete structural information mining of hidden Markov model.In the process of using the Baum-Welch algorithm,the double-layer hidden Markov model regards the part-of-speech sequence as an observation sequence,and extracts more information and maximizes the probability of the part-of-speech sequence through the Baum-Welch algorithm,which is more suitable for the actual situation.made corresponding changes.The model is cross-validated with 10 folds on the Penn Treebank corpus and the Groningen Meaning Bank corpus,and compared with traditional first-order and second-order hidden Mar-kov models.The results show that the double-layer hidden Markov model has a higher accuracy of part-of-speech tagging than the traditional first-order and second-order hidden Markov models.关键词
隐马尔可夫模型/Baum-Welch算法/词性标注/Viterbi算法/双层隐马尔可夫模型Key words
hidden Markov model/Baum-Welch algorithm/part-of-speech tagging/Viterbi algorithm/double-layer hid-den Markov model分类
信息技术与安全科学引用本文复制引用
赖威,金忠..基于双层隐马尔可夫模型的英文词性标注研究[J].计算机与数字工程,2025,53(5):1226-1229,1268,5.
