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Recall is the Proper Evaluation Metric for Word Segmentation
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Taipeo: Asian Federation of Natural Language Processing, 2017. 86-90 p.
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:uu:diva-335946OAI: oai:DiVA.org:uu-335946DiVA: diva2:1164403
Conference
The Eighth International Joint Conference on Natural Language Processing
Available from: 2017-12-11 Created: 2017-12-11 Last updated: 2018-01-13

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