Abstract
Ancient oracle bone inscriptions (OBIs) are important Chinese cultural artefacts, which are difficult and time-consuming to decipher even by the most expert paleographers and, as a result, a large proportion of excavated OBIs remain unidentified. In practice, OBIs are deciphered by translating between different writing systems; Chinese writing systems have evolved over time and ancient OBIs can be deciphered by translating their inscriptions to a known inscription in an adjacent writing system, but this is a complex and time-consuming process. In this paper we propose a novel case-based system, to support this task, allowing a paleographer to present an unknown inscription (image) as a query, to receive a set of similar images from an adjacent writing system with associated scholarly information, and so help guide the deciphering of the query. One important contribution of this work involves the use of an auto-encoder to learn suitable image representations to capture the relationship between two adjacent writing systems. We demonstrate the effectiveness of this approach using a novel, purpose-built case base, and discuss its use in a paleographic setting.
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This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number 12/RC/2289_P2. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
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Zhang, G., Liu, D., Smyth, B., Dong, R. (2021). Deciphering Ancient Chinese Oracle Bone Inscriptions Using Case-Based Reasoning. In: Sánchez-Ruiz, A.A., Floyd, M.W. (eds) Case-Based Reasoning Research and Development. ICCBR 2021. Lecture Notes in Computer Science(), vol 12877. Springer, Cham. https://doi.org/10.1007/978-3-030-86957-1_21
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