5 citations · 10 across the 6 of their papers we have counts for
6 papers
Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation
Zhao-Yang Liu, Liucheng Sun, Chenwei Weng +2
Bundle recommendation aims to provide a bundle of items to satisfy the user preference on e-commerce platform. Existing successful solutions are based on the contrastive graph lear…
Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs
Zequn Sun, Jiacheng Huang, Jinghao Lin +3
In this paper, we present the ``joint pre-training and local re-training'' framework for learning and applying multi-source knowledge graph (KG) embeddings. We are motivated by the…
What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
Zequn Sun, Jiacheng Huang, Xiaozhou Xu +3
Joint representation learning over multi-sourced knowledge graphs (KGs) yields transferable and expressive embeddings that improve downstream tasks. Entity alignment (EA) is a crit…
Deep Active Alignment of Knowledge Graph Entities and Schemata
Jiacheng Huang, Zequn Sun, Qijin Chen +3
Knowledge graphs (KGs) store rich facts about the real world. In this paper, we study KG alignment, which aims to find alignment between not only entities but also relations and cl…
Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data
Jiacheng Huang, Yao Zhao, Wei Hu +5
Knowledge graphs (KGs) have become a valuable asset for many AI applications. Although some KGs contain plenty of facts, they are widely acknowledged as incomplete. To address this…
Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection
Ben Chen, Bin Chen, Dehong Gao +5
With the pandemic of COVID-19, relevant fake news is spreading all over the sky throughout the social media. Believing in them without discrimination can cause great trouble to peo…