MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction.

ABSTRACT: Considering that the traditional deep learning event extraction method ignores the correlation between word features and sequence information, it cannot fully explore the hidden associations between events and events and between events and primary attributes. To solve these problems, we developed a new framework for event extraction called the masked attention-guided dynamic graph aggregation network. On the one hand, to obtain effective word representation and sequence representation, an interaction and complementary relationship are established between word vectors and character vectors. At the same time, a squeeze layer is introduced in the bidirectional independent recurrent unit to model the sentence sequence from both positive and negative directions while retaining the local spatial

SUBMITTER: Zhang G 

PROVIDER: S-EPMC11567535 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature