13 citations · 27 across the 3 of their papers we have counts for
5 papers
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization
Zhongfen Deng, Hao Peng, Dongxiao He +2
The current state-of-the-art model HiAGM for hierarchical text classification has two limitations. First, it correlates each text sample with all labels in the dataset which contai…
Hierarchical Bi-Directional Self-Attention Networks for Paper Review Rating Recommendation
Zhongfen Deng, Hao Peng, Congying Xia +3
Review rating prediction of text reviews is a rapidly growing technology with a wide range of applications in natural language processing. However, most existing methods either use…
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
Shen Wang, Jibing Gong, Jinlong Wang +4
Massive open online courses are becoming a modish way for education, which provides a large-scale and open-access learning opportunity for students to grasp the knowledge. To attra…
Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
Hao Peng, Jianxin Li, Qiran Gong +4
Events are happening in real-world and real-time, which can be planned and organized occasions involving multiple people and objects. Social media platforms publish a lot of text m…
Building Program Vector Representations for Deep Learning
Lili Mou, Ge Li, Yuxuan Liu +4
Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated feature…