activity
20192022
most citedKnowledge Perceived Multi-modal Pretraining in E-commerce

21 citations · 94 across the 16 of their papers we have counts for

collaborators

21 papers

cs.CL20225 cited

On Analyzing the Role of Image for Visual-enhanced Relation Extraction

Lei Li, Xiang Chen, Shuofei Qiao +3

Multimodal relation extraction is an essential task for knowledge graph construction. In this paper, we take an in-depth empirical analysis that indicates the inaccurate informatio…

cs.AI20226 cited

Neural-Symbolic Entangled Framework for Complex Query Answering

Zezhong Xu, Wen Zhang, Peng Ye +2

Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of the KG incompleteness issue and cascading errors during reasoning. Recent query…

cs.LO20221 cited

Ruleformer: Context-aware Differentiable Rule Mining over Knowledge Graph

Zezhong Xu, Peng Ye, Hui Chen +3

Rule mining is an effective approach for reasoning over knowledge graph (KG). Existing works mainly concentrate on mining rules. However, there might be several rules that could be…

cs.CL20226 cited

Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting

Mingyang Chen, Wen Zhang, Zhen Yao +4

We study the knowledge extrapolation problem to embed new components (i.e., entities and relations) that come with emerging knowledge graphs (KGs) in the federated setting. In this…

cs.AI2022

Deep Reinforcement Learning for Entity Alignment

Lingbing Guo, Yuqiang Han, Qiang Zhang +1

Embedding-based methods have attracted increasing attention in recent entity alignment (EA) studies. Although great promise they can offer, there are still several limitations. The…

cs.AI2022

PKGM: A Pre-trained Knowledge Graph Model for E-commerce Application

Wen Zhang, Chi-Man Wong, Ganqinag Ye +4

In recent years, knowledge graphs have been widely applied as a uniform way to organize data and have enhanced many tasks requiring knowledge. In online shopping platform Taobao, w…