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- W2897717436 abstract "The1 task of charge prediction is to decide accurate charges for a given case of crime. The relevant law texts play an important role in the work of charge prediction, and therefore we used an end-to-end memory network to perform the charge prediction. We combine the supportive law articles from the statutory laws and regulations with the large external memory, which can be trained without requiring significantly more supervision. Several experimental results demostrate that neural networks taking the Position Embeddings (pF), Part-of-speech tag Embeddings (POSF), the WordNet (WN) and bigram information as input can get better result than previous other methods." @default.
- W2897717436 created "2018-10-26" @default.
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- W2897717436 date "2018-10-22" @default.
- W2897717436 modified "2023-10-16" @default.
- W2897717436 title "Legal Article-Aware End-To-End Memory Network for Charge Prediction" @default.
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- W2897717436 doi "https://doi.org/10.1145/3207677.3278068" @default.
- W2897717436 hasPublicationYear "2018" @default.
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