3 papers
cs.CL2022
Exploring Entity Interactions for Few-Shot Relation Learning (Student Abstract)
YI Liang, Shuai Zhao, Bo Cheng +2
Few-shot relation learning refers to infer facts for relations with a limited number of observed triples. Existing metric-learning methods for this problem mostly neglect entity in…
cs.CL2021
Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering
Xu Wang, Shuai Zhao, Bo Cheng +5
Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities. Although effective, most o…
cs.SI2019
motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks
Manoj Reddy Dareddy, Mahashweta Das, Hao Yang
Recent years have witnessed a surge of interest in machine learning on graphs and networks with applications ranging from vehicular network design to IoT traffic management to soci…