Real-word error correction with trigrams: correcting multiple errors in a sentence.
Spelling correction is a fundamental task in text mining. In this study, we assess the real-word error correction model proposed by Mays, Damerau and Mercer and describe several drawbacks of the model. We propose a new variation which focuses on detecting and correcting multiple real-word errors in...
| Publicado en: | Language Resources & Evaluation Vol. 52; no. 2; pp. 485 - 503 |
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| Formato: | Artículo |
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Springer Nature
Jun2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Spelling correction is a fundamental task in text mining. In this study, we assess the real-word error correction model proposed by Mays, Damerau and Mercer and describe several drawbacks of the model. We propose a new variation which focuses on detecting and correcting multiple real-word errors in a sentence, by manipulating a probabilistic context-free grammar to discriminate between items in the search space. We test our approach on the Wall Street Journal corpus and show that it outperforms Hirst and Budanitsky’s WordNet-based method and Wilcox-O’Hearn, Hirst, and Budanitsky’s fixed windows size method. |
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