Research Article
Using Deep Learning to Predict Sentiments: Case Study in Tourism
| | Model | Model description |
| | 1 | (582) embedding→(582 × 300) LSTM→(30) dense [sigmoid]→(1) | | 2 | (582) embedding→(582 × 300) LSTM→(50) dense [sigmoid]→(1) | | 3 | (582) embedding→(582 × 300) LSTM→(70) dense [sigmoid]→(1) | | 4 | (582) embedding→(582 × 300) LSTM→(100) dense [sigmoid]→(1) | | 5 | (582) embedding→(582 × 300) LSTM→(200) dense [sigmoid]→(1) | | 6 | (582) embedding→(582 × 300) LSTM→(300) dense [sigmoid]→(1) | | 7 | (582) embedding→(582 × 300) LSTM→(500) dense [sigmoid]→(1) | | 8 | (582) embedding→(582 × 300) Conv1D→(575 × 64) MaxPooling1D→(287 × 64) flatten→(18,368) dense [relu]→(10) dense [sigmoid]→(1) | | 9 | (582) embedding→(582 × 300) Conv1D→(575 × 128) MaxPooling1D→(287 × 128) flatten→(36,736) dense [relu]→(10) dense [sigmoid]→(1) | | 10 | (582) embedding→(582 × 300) Conv1D→(575 × 32) MaxPooling1D→(287 × 32) Conv1D→(280 × 64) flatten→(17,920) dense [relu]→(10) dense [sigmoid]→(1) | | 11 | (582) embedding→(582 × 300) Conv1D→(582 × 32) MaxPooling1D→(291 × 32) LSTM→(100) dense [sigmoid]→(1) |
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