Towards Understanding the Geometry of Knowledge Graph Embeddings理解
Chandrahas et al. 2018 ACL. 论文背景 知识图谱的embedding方式有多种，可按得分函数(score function)的计算表达式分为“加法模型”和“乘法模型”两类（见下图1）。本文提出新的度量指标，研究各种embedding方式的几何(geometry)性质。 图1：知识图谱embedding得分函数分类 度量指标 ATM(alignment to mean):
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相关文章
- 1. 论文理解—— DisenE: Disentangling Knowledge Graph Embeddings
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- 9. 论文解读：Connecting Embeddings for Knowledge Graph Entity Typing
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