计算机科学 ›› 2022, Vol. 49 ›› Issue (3): 276-280.doi: 10.11896/jsjkx.211100249
缪峰1, 王萍2, 李太勇2
MIU Feng1, WANG Ping2, LI Tai-yong2
摘要： 抽取事件之间的因果关系能够应用于自动问答、知识提取、常识推理等方面。隐式因果关系由于缺乏明显的词汇特征和中文复杂的句法结构,使得其抽取极为困难,已成为当前研究的难点。相比而言,显示因果关系的抽取比较容易、准确率高,且因果关系事件之间的逻辑关系稳定。为此,文中提出了一种原创的方法,首先通过对抽取的显示因果事件对进行事件动作的归一化处理后形成事件方向,然后对事件主体进行泛化处理,最终形成标准的匹配因果事件对集合。利用此集合根据事件相似度从语句中抽取隐式因果事件对。为了识别更多的隐式因果关系,文中同时提出了一种因果连接词发现算法。在网易财经、腾讯财经和新浪财经上爬取的实验数据验证,对事件动作进行归一化处理后形成事件方向相比传统方法抽取准确率提高了1.02%。
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