Machine learning and data analysis for word segmentation of classical Chinese poems: illustrations with Tang and Song examples.

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 par...

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Publicado en:Digital Scholarship in the Humanities Vol. 39; no. 1; pp. 228 - 242
Autores principales: Liu, Chao-Lin, Chang, Wei-Ting, Chu, Chang-Ting, Zheng, Ti-Yong
Formato: Artículo
Publicado: Oxford University Press / USA Apr2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Machine learning and data analysis for word segmentation of classical Chinese poems: illustrations with Tang and Song examples.
      aug:
        au:
          Liu, Chao-Lin
          Chang, Wei-Ting
          Chu, Chang-Ting
          Zheng, Ti-Yong
        affil:
          Department of Computer Science, National Chengchi University , 64 Chih-Nan Road Section 2 , Wen-Shan, Taipei 116011, Taiwan
          Department of Computer Science and Engineering, University of California at Riverside , 900 University Avenue , Riverside, California 92521, United States
          Department of Electrical Engineering, National Yang Ming Chiao Tung University , 1001 University Road , East, Hsinchu 300093, Taiwan
      su:
        Chinese language
        Machine learning
        Data analysis
        Poetry (Literary form)
        Chinese literature
        Music charts
      sug:
        subj:
          Chinese language
          Machine learning
          Data analysis
          Poetry (Literary form)
          Chinese literature
          Music charts
      keyword:
        classical Chinese poems
        digital humanities
        unsupervised learning
        word segmentation
      ab: 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.
      pubtype: Academic Journal
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    language: English
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