阅读和尝试理解 TripleRE: Knowledge Graph Embeddings via triple Relation Vectors
文章来源
在open graph benchmark的比赛中,360 的模型在数据集ogbl-wikikg2 上拿了第一和第三，所以把论文拿过来看看
第一名的文章链接：
TripleRE: Knowledge Graph Embeddings via triple Relation Vectors
尝试理解和阅读文章
Introduction
在这里文中提到
Our work mainly lies in the optimization of the Translation distance model. One major theoretical issue that has dominated the field for many years concerns how to model the complex relation.
However, pairRE still only regards the relationship as the projection of the node. We believe that both pairRE and Rotate does not take account of the relationship can learn as the translation part of the node.
在文中，360 的模型将relationship 分解成了三个部分
We split the relationship into three parts.
- The projection part is the same as PairRE
- The translation part is learned by a separate parameter.
- 然后第三个部分好像没有明说(也可能是我没找到 QAQ)
不过在这个地方着重说明了TripleRe + NodePiece 效果是最好的
Related Work
先不谈，都是前人的工作
Methodology
Loss Function
Score Function
Conclusions and Future Work
这篇文章主要就是证明了distance-based knowledge representation model 也可以学习比较复杂的knowledge representation vectors
以后想到再补充