[論文筆記]A Scalable Neural Shortlisting-Reranking Approach for Large-Scale Domain Classification in NLU
這篇論文提出一種大規模訓練的智能對話模型。模型有兩層結構，第一層(Shortlisting)用來選出幾個機率最大的domain，並判別intent，第二層(Hypothesis Reranker)用歷史的記錄，找出機率最大的intent。 Shortlisting模型，主要是用character和word-level的資訊，放入LSTM中，去選出前k機率大的domain。再分別依據不同的domai
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