This research uses NLP algorithms (Word2Vec, GloVe, and BERT) to analyze semantic similarities among five English translations of *The Analects*. A corpus was built from these translations, and the algorithms assessed sentence-level semantic congruence. Findings revealed semantic variations, categorizing sentence pairs as "Abnormal," "High-similarity," and "Low-similarity." Core concepts and personal names significantly impacted semantic representation. The study aims to improve readers' understanding and offer translation strategies.
Publisher
Humanities and Social Sciences Communications
Published On
Jan 05, 2024
Authors
Liwei Yang, Guijun Zhou
Tags
NLP
semantic analysis
translations
The Analects
Word2Vec
GloVe
BERT
Related Publications
Explore these studies to deepen your understanding of the subject.
