Graph Convolutional Network

Dynamic graph embedding has gained great attention recently due to its capability of learning low-dimensional and meaningful graph representations for complex temporal graphs with high accuracy. However, recent advances mostly focus on learning node …

Text classification has become a key operation in various natural language processing tasks. The efficiency of most classification algorithms predominantly confide in the quality of input features. In this work, we propose a novel multi-class text …