@inproceedings{li-etal-2023-rong,
    title = "融合汉越关联关系的多语言事件观点对象识别方法(A Multilingual Event Opinion Target Recognition Method Incorporating {C}hinese and {V}ietnamese Association Relations)",
    author = "Li, Gege  and
      Guo, Junjun  and
      Xu, Zhengtao  and
      Xiang, Yan",
    editor = "Sun, Maosong  and
      Qin, Bing  and
      Qiu, Xipeng  and
      Jiang, Jing  and
      Han, Xianpei",
    booktitle = "Proceedings of the 22nd Chinese National Conference on Computational Linguistics",
    month = aug,
    year = "2023",
    address = "Harbin, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://aclanthology.org/2023.ccl-1.3",
    pages = "31--42",
    abstract = "{``}越南语观点对象识别是越南语事件观点分析的重要研究内容。由于汉越两种语言的语法结构上存在差异,使得多语言事件关联复杂,观点对象表征困难。现有研究方法仅能实现汉越双语的表征,未能有效捕获并利用汉越双语事件中要素的关联关系。因此,本文提出一种融合汉越关联关系的多语言事件观点对象识别方法,利用中文和越南语事件间的要素共现和整体语义关联构建汉越多语言事件表征网络,使用多语言预训练语言模型获得要素节点的特征向量,利用图卷积网络对节点信息进行聚合,得到同一语义空间下汉越双语的公共表征,实现汉越事件观点对象的识别。实验结果表明本文模型能够更有效地构建多语言关联信息,其F1值较多个基线模型都有明显提高。{''}",
    language = "Chinese",
}