Towards Understanding the Geometry of Knowledge Graph Embeddings理解
Chandrahas et al. 2018 ACL. 論文背景 知識圖譜的embedding方式有多種，可按得分函數(score function)的計算表達式分爲「加法模型」和「乘法模型」兩類（見下圖1）。本文提出新的度量指標，研究各種embedding方式的幾何(geometry)性質。 圖1：知識圖譜embedding得分函數分類 度量指標 ATM(alignment to mean):
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相關文章
- 1. 論文理解—— DisenE: Disentangling Knowledge Graph Embeddings
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- 5. Towards Understanding Google Titan
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