Automatic Translating Between Ancient Chinese and Contemporary Chinese with Limited Aligned Corpora
Table 2: Evaluation of logarithmic linear models and our method.
['[BOLD] Features', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1-score']
Our proposal algorithm does not use the features of sentence lengths and matching pattern. If we only adopt the feature of Co-occurrence, the performance of our proposal is 1.1% higher on F1-score than that of the supervised baseline (98.3%). To conclude, our proposal algorithm uses fewer features and use no training data but perform better than the supervised baseline.