31 citations · 94 across the 10 of their papers we have counts for
14 papers · 2 filters
Unsupervised Machine Commenting with Neural Variational Topic Model
Shuming Ma, Lei Cui, Furu Wei +1
Article comments can provide supplementary opinions and facts for readers, thereby increase the attraction and engagement of articles. Therefore, automatically commenting is helpfu…
A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification
Pengcheng Yang, Shuming Ma, Yi Zhang +3
Multi-label text classification (MLTC) aims to assign multiple labels to each sample in the dataset. The labels usually have internal correlations. However, traditional methods ten…
LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
Shuming Ma, Lei Cui, Damai Dai +2
We introduce the task of automatic live commenting. Live commenting, which is also called `video barrage', is an emerging feature on online video sites that allows real-time commen…
Identifying High-Quality Chinese News Comments Based on Multi-Target Text Matching Model
Deli Chen, Shuming Ma, Pengcheng Yang +1
With the development of information technology, there is an explosive growth in the number of online comment concerning news, blogs and so on. The massive comments are overloaded,…
Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification
Junyang Lin, Qi Su, Pengcheng Yang +2
We propose a novel model for multi-label text classification, which is based on sequence-to-sequence learning. The model generates higher-level semantic unit representations with m…
SGM: Sequence Generation Model for Multi-label Classification
Pengcheng Yang, Xu Sun, Wei Li +3
Multi-label classification is an important yet challenging task in natural language processing. It is more complex than single-label classification in that the labels tend to be co…