Proceedings of the 2015 3rd International Conference on Education, Management, Arts, Economics and Social Science 2016
DOI: 10.2991/icemaess-15.2016.287
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Research and realization of Chinese text semantic correction Based on Rule

Abstract: Automatic correction is an important research field in natural language processing, it is still relatively weak in the text automatic correction technology on semantic level. This paper presents develop XML rules based on LanguageTool Chinese grammar correction, match error correction in semantic level for the content of the rule to write the corresponding rule base, and realize automatic detect the corresponding content of semantic error in the text, and put forward the corresponding modification suggestions … Show more

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Cited by 2 publications
(2 citation statements)
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“…The existing CGED models do not consider the characteristics of semantic errors related to syntactic dependency. Some researchers try to solve CSER based on rules (Wu et al, 2015) and the Semantic Knowledge-base (Guan and Zhang, 2012;Zhang et al, 2021). However, the traditional method is powerless for some more complex and obscure semantic errors.…”
Section: Text Error Detectionmentioning
confidence: 99%
“…The existing CGED models do not consider the characteristics of semantic errors related to syntactic dependency. Some researchers try to solve CSER based on rules (Wu et al, 2015) and the Semantic Knowledge-base (Guan and Zhang, 2012;Zhang et al, 2021). However, the traditional method is powerless for some more complex and obscure semantic errors.…”
Section: Text Error Detectionmentioning
confidence: 99%
“…By reading a large number of documents and the survey found that political class information is a semantic level is relatively easy to make mistakes and difficult to detect. And semantic logic errors have four major characteristics: territoriality, nature, concealment and severity [8]. The semantic logic reasoning can solve the problem of logical reasoning missing at the semantic level.…”
Section: Requirements Analysismentioning
confidence: 99%