[论文笔记]A Scalable Neural Shortlisting-Reranking Approach for Large-Scale Domain Classification in NLU
这篇论文提出一种大规模训练的智能对话模型。模型有两层结构，第一层(Shortlisting)用来选出几个几率最大的domain，并判别intent，第二层(Hypothesis Reranker)用历史的记录，找出几率最大的intent。 Shortlisting模型，主要是用character和word-level的资讯，放入LSTM中，去选出前k几率大的domain。再分别依据不同的domai
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