Research Article
Learning Users’ Intention of Legal Consultation through Pattern-Oriented Tensor Decomposition with Bi-LSTM
Table 2
F1 score of algorithms based on multiple deep neural networks.
| Optimization | Basic algorithm | TextCNN | TextCNN attention | TextRNN | TextRNN attention | LSTM | BiLSTM | GRU | Bi-GRU |
| The original method | 0.64 | 0.70 | 0.68 | 0.71 | 0.70 | 0.74 | 0.71 | 0.77 | CP TP method | 0.72 | 0.77 | 0.80 | 0.78 | 0.83 | 0.87 | 0.83 | 0.84 | Tucker TP method | 0.75 | 0.77 | 0.76 | 0.81 | 0.80 | 0.84 | 0.82 | 0.86 | Pattern-oriented TP | 0.83 | 0.85 | 0.84 | 0.86 | 0.88 | 0.92 | 0.86 | 0.89 |
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