A Correcting Model Based on Tribayes for Real-Word Errors in English Essays

Ya Zhou, Shenghao Jing, Guimin Huang, Shaozhong Liu, Yan Zhang
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引用次数: 9

Abstract

This paper addresses the problem of real-word spelling errors, and also the problem of omission of effective features due to deficiency of training set in spelling correction. then a method called RCW (real-word correction with Word Net) based on Tribayes is introduced, and it solves these problems to a certain extent. Drawing upon the context information, the score of ambiguous words are calculated and regarded as decisive factor for real-word errors correction in RCW. Moreover, the synonyms of the effective features ignored are extracted from Word Net, and we use them as feature so as to improve the accuracy of real-word errors correction. Experiment shows that RCW is able to provide a better performance than Microsoft Word 2007 on real-word errors correction.
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基于Tribayes的英语作文实词错误纠错模型
本文解决了真实单词拼写错误的问题,同时也解决了拼写纠正中由于训练集不足而导致有效特征缺失的问题。然后介绍了一种基于Tribayes的实时单词校正方法RCW (real-word correction with Word Net),在一定程度上解决了这些问题。根据上下文信息,计算歧义词的得分,并将其作为RCW中实词纠错的决定性因素。此外,从wordnet中提取被忽略的有效特征的同义词,并将其作为特征使用,以提高实际单词纠错的准确性。实验表明,RCW能够提供比Microsoft Word 2007更好的实词纠错性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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