基于深度信念网络的维吾尔语事件伴随关系识别

Identifying Accompanying Relationship between Uyghur Events Based on Deep Belief Network

维吾尔语事件伴随关系是维吾尔语语言中常见且重要的关系之一。结合对维吾尔语语言特点的研究,该文提出一种基于深度信念网络的维吾尔语事件伴随关系识别方法,根据维吾尔语语言特性和事件伴随关系的特点,抽取12项基于事件结构信息的特征;同时充分利用事件对所对应的两个触发词之间的语义信息,引入Word Embedding计算两个触发词之间的语义相似度。而后融合两类特征作为DBN模型的输入进行训练,最后将训练结果作为softmax分类器的输入实现维吾尔语事件伴随关系的识别。该方法用于维吾尔语事件伴随关系的识别准确率P为81.89%、召回率R为84.32%、F1值为82.48%。实验结果表明,与支持向量机方法相比,基于DBN模型的方法取得更好的识别效果。

The accompanying relationship between the events is common in the Uyghur language.This paper proposes a method to identify the accompanying relationship between the Uyghur events based on deep belief network（Deep Belief Network,DBN）.According to the characteristics of the Uyghur language,this paper extract 12 features which are based on the event structure information;It also applies the Word Embedding to calculate the semantic similarity between the two trigger words.The experiments show that the precision rate,the recall rate and F value of the proposed method reach 81.89%,84.32% and 82.48%,respectively,which outperforms SVM（Support Vector Machine,SVM）.