其中,N-ary Tree-LSTM适合于二叉树,而Child-Sum Tree-LSTM适用于多孩子的无序树,并且具有更高的计算效率。 在此工作的基础上,Yang等人[18]提出了一种基于AST编码的跨指令集架构的检测方法Asteria。通过提取二进制函数的AST作为跨指令集架构的二进制特征来源,并利用能够处理树形数据的Tree-LSTM网络学习二进制代码的...
Methods: In this study, we introduce an attention mechanism into Child-Sum Tree-LSTMs for the detection of biomedical event triggers. We incorporate previous researches on assigning attention weights to adjacent nodes and integrate this mechanism into Child-Sum Tree-LSTMs ...