Recall is the Proper Evaluation Metric for Word Segmentation
2017-11-01IJCNLP 2017Unverified0· sign in to hype
Yan Shao, Christian Hardmeier, Joakim Nivre
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We extensively analyse the correlations and drawbacks of conventionally employed evaluation metrics for word segmentation. Unlike in standard information retrieval, precision favours under-splitting systems and therefore can be misleading in word segmentation. Overall, based on both theoretical and experimental analysis, we propose that precision should be excluded from the standard evaluation metrics and that the evaluation score obtained by using only recall is sufficient and better correlated with the performance of word segmentation systems.