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Mar, 2024
基于关系图神经网络的不确定性感知的少样本知识图谱补全
Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion
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Qian Li, Shu Guo, Yingjia Chen, Cheng Ji, Jiawei Sheng...
TL;DR
通过利用高斯分布对有限数据进行建模,我们提出了一种新颖的不确定性感知少样本知识图完成框架(UFKGC),该框架能更好地理解有限数据并提高鲁棒性,实验证明与竞争对手相比,在两个基准数据集上取得了出色的性能。
Abstract
few-shot knowledge graph completion
(FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the
uncertainty
of entities and triples may limi
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