Computer Engineering, Volume. 51, Issue 8, 160(2025)

Research on Cross-Language Summarization in Chinese-Burmese-Vietnamese Based on Enhanced Linguistic Relationships

He Zhilei1,2, Gao Shengxiang1,2、*, Zhu Enchang1,2, and Yu Zhengtao1,2
Author Affiliations
  • 1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
  • 2Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming 650500, China
  • show less
    References(25)

    [1] [1] ZHU J N, WANG Q, WANG Y N, et al. NCLS: Neural Cross-Lingual Summarization[C]. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics; 2019: 3054-3064. doi: 10.18653/v1/D19-1302

    [2] [2] ZHANG J J, ZHOU Y, ZONG C Q. Abstractive cross-language summarization via translation model enhanced predicate argument structure fusing[J]. ACM Transactions on Audio, Speech, and Language Processin-g. 2016: 24(10): 1842-1853.

    [3] [3] OUYANG J, SONG B, MCKEOWN K. A robust abstractive system for cross-lingual summarization[C]. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019: 2025-2031.

    [4] [4] SEE A, LIU P J, MANNING C D. Get to the point: Summarization with pointer-generator networks[C]. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2017: 1073-1083.

    [5] [5] LEUSKI A, LIN C Y, ZHOU L, GERMANN U, OCH F J, HOVY E. Cross-Lingual C*ST*RD: English Access to Hindi Information[J]. ACM Transactions on Asian Language Information Processing. 2003; 2(3): 245-269. doi: 10.1145/979872.979877.

    [6] [6] BOUDIN F, HUET S, TORRES-MORENO J M. A graph-based approach to cross-language multi-document summarization[J]. Polibits. 2011; (43): 113-118.

    [7] [7] PAGE L, BRIN S, MOTWANI R, WINOGRAD T. The PageRank Citation Ranking: Bringing Order to the Web[C]. In: The Web Conference.; 1999. https://api.semanticscholar.org/CorpusID:1508503.

    [8] [8] WAN X J. Using Bilingual Information for Cross-Language Document Summarization[C]. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1. HLT’11. Association for Computational Linguistics; 2011: 1546-1555.

    [9] [9] ORSAN C, CHIOREAN O A. Evaluation of a Cross-lingual Romanian-English Multi-document Summariser[C]. Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC, 08). European Language Resources Association (ELRA). 2008. http://www.lrec-conf.org/proceedings/lrec2008/pdf/539_paper.pdf.

    [10] [10] WAN X J, LI H Y, XIAO J G. Cross-Language Document Summarization Based on Machine Translation Quality Prediction[C]. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. 2010: 917-926. https://aclanthology.org/P10-1094.

    [11] [11] CORTES C, VAPNIK V. Support-vector networks[J]. Machine learning. 1995; 20: 273-297.

    [12] [12] ZHU J N, ZHOU Y, ZHANG J J, ZONG C Q. Attend, Translate and Summarize: An Efficient Method for Neural Cross-Lingual Summarization[C]. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics; 2020: 1309-1321. doi: 10.18653/v1/2020.acl-main.121.

    [13] [13] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need[C]. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems, 2017: 5998-6008.

    [14] [14] DYER C, CHAHUNEAU V, SMITH N A. A simple, fast, and effective reparameterization of IBM model 2[C]. Proceedings of the 2013 Conference of the Nort-h American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2013: 644-648.

    [15] [15] JIANG S, TU D, CHEN X, TANG R, WANG W, WANG H. ClueGraphSum: Let Key Clues Guide the Cross-Lingual Abstractive Summarization[EB/OL]. Published online 2022.

    [16] [16] MIHALCEA R, TARAU P. TextRank: Bringing Order into Text[C]. Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing. A-ssociation for Computational Linguistics; 2004: 404-411. https://aclanthology.org/W04-3252.

    [18] [18] STANTON S, IZMAILOV P, KIRICHENKO P, ALEMI A A, WILSON A G. Does knowledge distillation really work?[J]. Advances in Neural Information Processing Systems. 2021; 34: 6906-6919.

    [19] [19] AYANA, SHEN S Q, CHEN Y, YANG C, LIU Z Y, SUN M S. Zero-Shot Cross-Lingual Neural Headline Generation[J]. IEEE/ACM Transactions on Audio, Sp-eech, and Language Processing. 2018; 26(12): 2319-2327. doi: 10.1109/TASLP.2018.2842432.

    [20] [20] CHO K, VAN M B, GULCEHRE C, et al. Learning Phrase Representations using RNN Encoder - Decoder for Statistical Machine Translation[C]. In: Moschitti A, Pang B, Daelemans W, eds. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics; 2014: 1724-1734. doi: 10.3115/v1/D14-1179.

    [22] [22] DUAN X Y, YIN M M, ZHANG M, CHEN B, LUO W H. Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attent-ion[C]. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Associati-on for Computational Linguistics; 2019: 3162-3172. doi: 10.18653/v1/P19-1305.

    [23] [23] NGUYEN T T, LUU A T. Improving neural cross-lingual abstractive summarization via employing optimal transport distance for knowledge distillation[C]. Proceedings of the AAAI Conference on Artificial Intelligence. Vol 36.; 2022: 11103-11111.

    [24] [24] PHAM K, LE K, HO N, PHAM T, BUI H. On unbalanced optimal transport: An analysis of sinkhorn algorithm. In: International Conference on Machine Learning. PMLR; 2020: 7673-7682.

    [25] [25] BAI Y, GAO Y, HUANG H Y. Cross-lingual abstractive summarization with limited parallel resources[C]. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021: 6910-6924.

    [26] [26] LIANG Y L, MENG F D, ZHOU C L, et al. A Vari-ational Hierarchical Model for Neural Cross-Lingual S-ummarization[C]. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics; 2022: 2088-2099. doi: 10.18653/v1/2022.acl-long.148.

    [27] [27] SOHN K, LEE H, YAN X C. Learning structured output representation using deep conditional generative models[C]. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems. 2015: 3483-3491.

    Tools

    Get Citation

    Copy Citation Text

    He Zhilei, Gao Shengxiang, Zhu Enchang, Yu Zhengtao. Research on Cross-Language Summarization in Chinese-Burmese-Vietnamese Based on Enhanced Linguistic Relationships[J]. Computer Engineering, 2025, 51(8): 160

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: --

    Accepted: Aug. 26, 2025

    Published Online: Aug. 26, 2025

    The Author Email: Gao Shengxiang (gaoshengxiang.yn@foxmail.com)

    DOI:10.19678/j.issn.1000-3428.0069057

    Topics