57 citations · 132 across the 16 of their papers we have counts for
4 papers · 1 filter
Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
Yufeng Zhang, Weiqing Wang, Hongzhi Yin +3
Inductive link prediction (ILP) is to predict links for unseen entities in emerging knowledge graphs (KGs), considering the evolving nature of KGs. A more challenging scenario is t…
Contrastive Learning with Bidirectional Transformers for Sequential Recommendation
Hanwen Du, Hui Shi, Pengpeng Zhao +5
Contrastive learning with Transformer-based sequence encoder has gained predominance for sequential recommendation. It maximizes the agreements between paired sequence augmentation…
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Xuefeng Xian +5
Sequential Recommendation aims to predict the next item based on user behaviour. Recently, Self-Supervised Learning (SSL) has been proposed to improve recommendation performance. H…
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks
Jiaan Wang, Beiqi Zou, Zhixu Li +4
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context. The key challenges of the task lie in…