activity
20192022
most citedKnowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation

20 citations · 25 across the 3 of their papers we have counts for

collaborators

7 papers

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…

cs.AI2021

Billion-scale Pre-trained E-commerce Product Knowledge Graph Model

Wen Zhang, Chi-Man Wong, Ganqiang Ye +3

In recent years, knowledge graphs have been widely applied to organize data in a uniform way and enhance many tasks that require knowledge, for example, online shopping which has g…

cs.CL20205 cited

Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

Xin Lv, Xu Han, Lei Hou +6

Multi-hop reasoning has been widely studied in recent years to seek an effective and interpretable method for knowledge graph (KG) completion. Most previous reasoning methods are d…

cs.CL2020

Neural Abstractive Summarization with Structural Attention

Tanya Chowdhury, Sachin Kumar, Tanmoy Chakraborty

Attentional, RNN-based encoder-decoder architectures have achieved impressive performance on abstractive summarization of news articles. However, these methods fail to account for…

cs.CL201920 cited

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation

Zequn Sun, Chengming Wang, Wei Hu +4

Graph neural networks (GNNs) have emerged as a powerful paradigm for embedding-based entity alignment due to their capability of identifying isomorphic subgraphs. However, in real…

cs.CL2019

Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs

Mingyang Chen, Wen Zhang, Wei Zhang +2

Link prediction is an important way to complete knowledge graphs (KGs), while embedding-based methods, effective for link prediction in KGs, perform poorly on relations that only h…