Volume 2, Issue 2
  • ISSN 1877-7031
  • E-ISSN: 1877-8798
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We address the issue of poetic discourse in classical Chinese poetry and propose the use of imageries as characteristic anchors that stylistically differentiate poetic schools as well as individual poets. We describe an experiment that is aimed at the use of ontological knowledge to identify patterns of imagery use as stylistic features of classical Chinese poetry for authorship attribution of classical Chinese poems. This work is motivated by the understanding that the creative language use by different poets can be characterised through their creative use of imageries which can be captured through ontological annotation. A corpus of lyric songs written by Liu Yong and Su Shi in the Song Dynasty is used, which is word segmented and ontologically annotated. State-of-the-art techniques in automatic text classification are adopted and machine learning methods applied to evaluate the performance of the imagery-based features. Empirical results show that word tokens alone can be used to achieve an accuracy of 87% in the task of authorship attribution between Liu Yong and Su Shi. More interestingly, ontological knowledge is shown to produce significant performance gains when combined with word tokens. This observation is reinforced by the fact that most of the feature sets with ontological annotation outperform the use of bare word tokens as features. Our empirical evidence strongly suggests that the use of imageries is a powerful indicator of poetic discourse that is characteristic of the two poets concerned in the study.


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