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Jan, 2024
PipeNet:基于语义修剪的知识图谱问答
PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs
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Ying Su, Jipeng Zhang, Yangqiu Song, Tong Zhang
TL;DR
通过引入显式的知识图谱可以改善问答系统,本研究提出了一种基于实体节点定位、剪枝和推理的流程以提高图推理的效率,并采用图注意力网络进行子图数据的推理。在CommonsenseQA和OpenBookQA上的实验结果证明了方法的有效性。
Abstract
It is well acknowledged that incorporating explicit
knowledge graphs
(KGs) can benefit
question answering
. Existing approaches typically follow a grounding-reasoning pipeline in which entity nodes are first groun
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