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- W3134349109 abstract "In essay marking, manual grading will waste a lot of manpower and material resources, and the subjective judgment of marking teachers is easy to cause unfair phenomenon. Therefore, this paper proposes an automatic essay grading model combining multi-channel convolution and LSTM. The model adds a dense layer after the embedding layer, obtains the weight assignment of text through softmax function, then uses the multi-channel convolutional neural network to extract the text feature information of different granularities, and the extracted feature information is fused into the LSTM to model the text. The model is experimented on the ASAP composition data set. The experimental results show that the model proposed in this paper is 6% higher than the strong baseline model, and the automatic scoring effect is improved to a certain extent.KeywordsAutomatic essay scoringMultichannel convolutionLong Short-Term Memory" @default.
- W3134349109 created "2021-03-15" @default.
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- W3134349109 date "2021-01-01" @default.
- W3134349109 modified "2023-09-24" @default.
- W3134349109 title "Automatic Essay Scoring Model Based on Multi-channel CNN and LSTM" @default.
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- W3134349109 doi "https://doi.org/10.1007/978-981-16-1160-5_26" @default.
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