Abstract
Writing a Tang-Dynasty poetry in Chinese is very popular and useful in the tradition Chinese culture education field, In this paper we use GitHub open sources “jieba” Algorithm for text segmentation of Chinese Tang Dynasty poetry and database methods to auto-generate Chinese old Tang-Dynasty poetry, focus on AI for education field and poetry making project, through Chinese word semantic matching, short sentence combination and verse rhyme pattern rules.
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References
GitHub Jieba. https://GitHub.com/fxsjy/jieba. Accessed 20 Oct 2019
Wang, L.: A Summary of Rhyming Constraints of Chinese Poems. Beijing Press, Beijing (2002)
GitHub Pinyin. https://GitHub.com/hotoo/pinyin. Accessed 4 Oct 2019
Yi, X., Li, R., Sun, M.: Generating Chinese classical poems with RNN encoder-decoder. In: Sun, M., Wang, X., Chang, B., Xiong, D. (eds.) CCL/NLP-NABD -2017. LNCS (LNAI), vol. 10565, pp. 211–223. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69005-6_18
Yi, X., Sun, M., Li, R., Li, W.: Automatic poetry generation with mutual reinforcement learning, pp. 3143–3153 (2018). https://doi.org/10.18653/v1/d18-1353
Yi, X., Li, R., Sun, M.: Chinese poetry generation with a salient-clue mechanism (2018)
Microsoft Asia Research Institute Duilian. http://duilian.msra.cn/jueju/intro.html
Jiang, L., Zhou, M.: Generating Chinese couplets using a statistical MT approach. In: The 22nd International Conference on Computational Linguistics, Manchester, England (2008)
Hai, Y.: Database Basic Principles and Applications Development Tutorials. Nanjing University Press, Nanjing (2017)
Luo, Y., Huang, Y.: Text steganography with high embedding rate: using recurrent neural networks to generate Chinese classic poetry, pp. 99–104 (2017). https://doi.org/10.1145/3082031.3083240
Yan, R., Jiang, H., Lapata, M.: Poet: automatic Chinese poetry composition through a generative summarization framework under constrained optimization. In: Proceedings of IJCAI (2013)
He, J., Zhou, M., Jiang, L.: Generating Chinese classical poems with statistical machine translation models. In: Proceedings of the 26 AAAI Conference on Artificial Intelligence (2012)
Zhang, X., Lapata, M.: Chinese poetry generation with recurrent neural networks. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 670–680 (2014)
Wang, Q., Luo, T., Wang, D., et al.: Chinese song iambics generation with neural attention based model. CoRR.abs/1604.06274 (2016)
Wang, Z., He, W., Wu, H., et al.: Chinese poetry generation with planning based neural network. arXiv preprint arXiv:1610.09889 (2016)
Yan, R., Li, C.T., Hu, X., et al.: Chinese couplet generation with neural network structures. In: Proceedings of Meeting of the Association for Computational Linguistics (2016)
Wei, W., Huang, W., Wang, J., Deng, Z.: Chinese classical poetry and couplet generation based on multi-task learning. J. Chin. Inf. Process. 33(11), 115–124 (2019)
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Yu, H., Li, ZX., Jiang, YY. (2020). Using GitHub Open Sources and Database Methods Designed to Auto-Generate Chinese Tang Dynasty Poetry. In: Tian, Y., Ma, T., Khan, M. (eds) Big Data and Security. ICBDS 2019. Communications in Computer and Information Science, vol 1210. Springer, Singapore. https://doi.org/10.1007/978-981-15-7530-3_32
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DOI: https://doi.org/10.1007/978-981-15-7530-3_32
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