Abstract
This paper represents a text mining-based analysis on Classical Chinese poetry in ancient Korea. We try to evaluate the relations between poems with several document similarity analysis methods, and also to estimate the quality of poems based on simple hypotheses. Nine poem books in the 15th century have been selected for analysis to validate the effectiveness of this approach. In order to overcome the limited number of data, we slightly change the existing similarity measure and try to adjust target data by considering the structure of Classical Chinese poetry. Analysis results show a high potential of this approach by producing outcomes that fairly match expectations.
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References
Classical Chinese poetry, Wikipedia. https://en.wikipedia.org/wiki/Classical_Chinese_poetry
tf–idf, Wikipedia. https://en.wikipedia.org/wiki/Tf-idf
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Institute for the translation of Korean classics, Korean classical literature integrated database. http://db.itkc.or.kr/
Acknowledgments
This paper was supported by Research Fund, Kumoh National Institute of Technology.
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Bekmirzaev, S., Lee, BC., Kim, TH. (2018). Pairwise Relation Analysis and Quality Estimation of Classical Chinese Poetry in Ancient Korea. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_119
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DOI: https://doi.org/10.1007/978-981-10-7605-3_119
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