【阅读笔记】Reasoning With Neural Tensor Networks for Knowledge Base Completion
前言 论文地址 Poster Abstract 这篇论文里，作者介绍了一个适用于推理两个实体关系的神经网络（Neural Tensor Network）.相比之前的工作要么将实体表示成离散的最小单元或者是单个的实体向量，而这篇论文实验表明当实体被表现成他们词向量的平均值时实验的效果会提升。最后，论文证明当这些词向量通过大量非监督学习的语料学习结果作为参数的初始化值，对于预测知识库里两个实体是否有关
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相关文章
- 1. End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion--阅读笔记
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