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Table 6 36 subtypes intent classification result

From: A benchmark dataset and case study for Chinese medical question intent classification

Model

Accuracy

TextCNN

0.473

TextRNN

0.424

Fast Text

0.462

TextGCN

0.357

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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