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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/149452

Title:	Machine learning and data analysis for word segmentation of classical Chinese poems: illustrations with Tang and Song examples
Authors:	劉昭麟 Liu, Chao-Lin;Chang, Wei-Ting;Chu, Chang-Ting;Zheng, Ti-Yong
Contributors:	資訊系
Date:	2024-04
Issue Date:	2024-01-29 09:45:29 (UTC+8)
Abstract:	Words are essential parts for understanding classical Chinese poems. We report a collection of 32,399 classical Chinese poems that were annotated with word boundaries. Statistics about the annotated poems support a few heuristic experiences, including the patterns of lines and a practice for the parallel structures (對仗), that researchers of Chinese literature discuss in the literature. The annotators were affiliated with two universities, so they could annotate the poems as independently as possible. Results of an inter-rater agreement study indicate that the annotators have consensus over the identified words 93 per cent of the time and have perfect consensus for the segmentation of a poem 42 per cent of the time. We applied unsupervised classification methods to annotate the poems in several different settings, and evaluated the results with human annotations. Under favorable conditions, the classifier identified about 88 per cent of the words, and segmented poems perfectly 22 per cent of the time.
Relation:	Digital Scholarship in the Humanities, Vol.39, No.1, pp.228–241,
Data Type:	article
DOI 連結:	https://doi.org/10.1093/llc/fqad073
DOI:	10.1093/llc/fqad073
Appears in Collections:	[資訊科學系] 期刊論文

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