Emotion Cause Extraction on Emotion Cause Corpus
77.21PrecisionCANN
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CANNArchitecture=Co-attention neural network2019.06 | 77.21 | 68.91 | 72.66 | |
| RTHNNumber of layers=32019.06 | 76.97 | 76.62 | 76.77 | |
| RTHNNumber of layers=12019.06 | 76.96 | 73.33 | 75.01 | |
| RTHNNumber of layers=22019.06 | 76.44 | 75.66 | 76.01 | |
| PAE-DGLFeatures=Relative position and dynamic global label2019.06 | 76.19 | 69.08 | 72.42 | |
| RTHNNumber of layers=42019.06 | 76.04 | 76.99 | 76.46 | |
| RTHNNumber of layers=52019.06 | 75.92 | 76.84 | 76.34 | |
| HCSArchitecture=CNN-RNN based three-level hierarchical network2019.06 | 73.88 | 71.54 | 72.69 | |
| MemnetArchitecture=Convolutional multiple-slot deep memory network2019.06 | 70.76 | 68.38 | 69.55 | |
| RBMethod Category=Rule-based2019.06 | 67.47 | 42.87 | 52.43 | |
| Multi-KernelMethod Type=Multi-kernel based2019.06 | 65.88 | 69.27 | 67.52 | |
| CNNArchitecture=Basic CNN2019.06 | 62.15 | 59.44 | 60.76 | |
| RB+CB+SVMClassifier=SVM, Features=Rules and Emotion Lexicon2019.06 | 59.21 | 53.07 | 55.97 | |
| RB+CBMethod Category=Combination2019.06 | 54.35 | 53.07 | 53.7 | |
| Word2vec+SVMClassifier=SVM, Features=Word2vec embeddings2019.06 | 43.01 | 42.33 | 41.36 | |
| Ngrams+SVMClassifier=SVM, Features=unigram, bigram, trigram2019.06 | 42 | 43.75 | 42.85 | |
| CBMethod Category=Common-sense based2019.06 | 26.72 | 71.3 | 38.87 |