TITLE:
Research on Translation Adaptation Strategy of Qilu Library Based on Transformer System
AUTHORS:
Tiantian Ping, Yiru Ge
KEYWORDS:
Qilu Library, Transformer System, AI Translation
JOURNAL NAME:
Open Access Library Journal,
Vol.13 No.3,
March
11,
2026
ABSTRACT: With the rapid development of artificial intelligence translation technology, the neural machine translation system based on the Transformer architecture has shown great potential in the translation of cultural classics. However, in the face of ancient books and documents, such as the “Qilu Library”, which are rich in regional culture, historical context and classical Chinese expression, the general translation model is often difficult to accurately convey its cultural depth and language style. This paper takes the Transformer system as the core, discusses its adaptation strategy in the translation process of “Qilu Library”, and focuses on analyzing the optimization path of the model in semantic understanding, cultural term processing, and language style conversion. The research combines corpus preprocessing, attention mechanism tuning, domain fine-tuning and manual post-editing, and proposes a set of “technology + humanities” dual-wheel-driven translation strategies for cultural classics, aiming to improve the cultural adaptability and communication effect of the translation. This study not only provides technical support for the international dissemination of Qilu culture, but also provides a replicable translation paradigm for the “going out” of excellent traditional Chinese culture.