关键词: 春秋三传, 异文, BERT, 自动发掘, 数字人文

Abstract: [Purpose/significance] Variations are a common phenomenon and also an important research object in ancient books. The traditional collation of ancient books is to manually search for materials, including variations from a large number of ancient books. This work is not only time-consuming, laborious, and heavy, but the data may not be accurate and comprehensive. Automatic mining of variant sentences through computers can obtain effective information from larger-scale corpus. In addition, the collation method combined with automatic mining of variant sentences can realize exhaustive retrieval, which is of great significance to the collation of ancient books. It provides new ideas and methods for the collation research of ancient books in the new period.[Method/process] This research automatically mined the variant sentences in Three Biographies of the Spring and Autumn Period, combining deep learning and introducing parallel corpus commonly used in the field of machine translation. Subsequently, this study compared LSTM and BERT models'results with the classic SVM model and further explored and analyzed the related content of the variants expressing the same event with different descriptions in two ancient books.[Result/conclusion] The experiment obtained a deep learning model for automatic mining of variants expressing the same event suitable for Three Biographies of the Spring and Autumn Period. It proves the feasibility of integrating new technologies such as deep learning into the construction of ancient books' knowledge base. Meanwhile, the combination of deep learning and parallel corpus can play a more significant role in studying variant sentences and provide practical support for applying digital humanities in the Chinese language and literature.

Key words: Three Biographies of the Spring and Autumn Period, variants, BERT, automatic mining, digital humanities