150 citations · 197 across the 8 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
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…
cs.AI2019★ 21 cited
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning
Wen Zhang, Bibek Paudel, Liang Wang +5
Reasoning is essential for the development of large knowledge graphs, especially for completion, which aims to infer new triples based on existing ones. Both rules and embeddings c…
cs.AI2019★ 150 cited
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
Wen Zhang, Bibek Paudel, Wei Zhang +2
Knowledge graph embedding aims to learn distributed representations for entities and relations, and is proven to be effective in many applications. Crossover interactions --- bi-di…