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Unsupervised Context-Sensitive Spelling Correction of Clinical Free-Text with Word and Character N-Gram Embeddings

机译：无监督的上下文敏感拼写校正临床自由文本与单词和字符n-gram嵌入的校正

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Pieter Fivez; Simon Suster; Walter Daelemans;
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1. Sentence Level N-Gram Context Feature in Real-Word Spelling Error Detection and Correction: Unsupervised Corpus Based Approach [J] . Tsegay Mullu Kassa Journal of Information Engineering and Applications . 2020,第4期

机译：句子级别n-gram上下文特征在实际单词拼写错误检测和校正中：基于无监督的语料库方法
2. Similarity-Based Unsupervised Spelling Correction Using BioWordVec: Development and Usability Study of Bacterial Culture and Antimicrobial Susceptibility Reports [J] . Taehyeong Kim, Sung Won Han, Minji Kang, JMIR Medical Informatics . 2021,第2期

机译：基于相似性的无监督拼写校正使用BioWordVec：细菌培养和抗微生物易感性报告的开发和可用性研究
3. Improving the reading of bisyllabic words that involve context-sensitive spelling rules: focus on successes or on failures? [J] . Esther G. Steenbeek-Planting, Wim H. J. van Bon, Robert Schreuder Reading and Writing . 2013,第9期

机译：改进涉及上下文敏感拼写规则的双音节单词的阅读：专注于成功还是失败？
4. Unsupervised Context-Sensitive Spelling Correction of Clinical Free-Text with Word and Character N-Gram Embeddings [C] . Pieter Fivez, Simon Suster, Walter Daelemans 16th workshop on biomedical natural language processing . 2017

机译：具有单词和字符N-Gram嵌入的临床自由文本的无监督上下文敏感拼写校正
5. A Method for Extracting Context-Sensitive Semantics of a Concept from a General-Purpose Corpus Using Word Embedding Space and Its Application [D] . Saxena, Aakash. 2020

机译：一种用词嵌入空间和应用程序从通用语料库中提取概念的上下文敏感语义的方法
6. Words prediction based on N-gram model for free-text entry in electronic health records [O] . Azita Yazdani, Reza Safdari, Ali Golkar, 2019

机译：基于N-GRAM模型的电子健康记录中自由文本输入的单词预测
7. Sentence Level N-Gram Context Feature in Real-Word Spelling Error Detection and Correction: Unsupervised Corpus Based Approach [O] . 2020

机译：句子级别n-gram上下文特征在实际单词拼写错误检测和校正中：基于无监督的语料库方法

Unsupervised Context-Sensitive Spelling Correction of Clinical Free-Text with Word and Character N-Gram Embeddings

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