Question Answering with Subgraph Embedding

时间 2020-12-30

标签知识图谱问答词嵌入子图嵌入繁體版

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Question Answering with Subgraph Embedding 总结文章提出一个将问题、候选答案映射到低维稠密向量，然后计算其关联程度评分，通过排序确定最后的答案。训练的过程是一个多任务训练过程，不仅使利用<问题、答案>对，也使用相同意思的问题对，来丰富词向量信息。候选答案的获取首先从问题中匹配出一个主题实体策略1：仅仅考虑与主题实体距离一跳以内的实体(有些问题的

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1. Question Answering with Subgraph Embeddings笔记
2. 【论文笔记】Question Answering with Subgraph Embeddings
3. Question Answering with Subgraph Embeddings【论文笔记】
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. Visual Question Answering with Memory-Augmented Networks
6. Character-Level Question Answering with Attention读书笔记
7. Open Question Answering with WeaklySupervised Embedding Models阅读笔记
8. Question Answering by Reasoning Across Documents with Graph Convolutional Networks
9. 【cs224n-7】Question Answering
10. Neural Generative Question Answering笔记

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