以深層類神經網路標記中文階層式多標籤語意概念 (Hierarchical Multi-Label Chinese Word Semantic Labeling using Deep Neural Network ) [In Chinese]

以深層類神經網路標記中文階層式多標籤語意概念 (Hierarchical Multi-Label Chinese Word Semantic Labeling using Deep Neural Network)

Hierarchical Chinese Legal event extraction via Pedal Attention Mechanism

Event extraction plays an important role in legal applications, including case push and auxiliary judgment. However, traditional event structure cannot express the connections between arguments, which are extremely impor…

Incorporating Deep Syntactic and Semantic Knowledge for Chinese Sequence Labeling with GCN

Recently, it is quite common to integrate Chinese sequence labeling results to enhance syntactic and semantic parsing. However, little attention has been paid to the utility of hierarchy and structure information encoded…

Translation as Cross-Domain Knowledge: Attention Augmentation for Unsupervised Cross-Domain Segmenting and Labeling Tasks

The nature of no word delimiter or inflection that can indicate segment boundaries or word semantics increases the difficulty of Chinese text understanding, and also intensifies the demand for word-level semantic knowled…

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

CNNs, RNNs, GCNs, and CapsNets have shown significant insights in representation learning and are widely used in various text mining tasks such as large-scale multi-label text classification. However, most existing deep …