With the continuous development of the Internet, more and more information enter people's lives. However, the information is mixed. It is difficult to guarantee the correctness of the text. For errors caused by homophone replacement, an automatic Chinese text local error detection and correction solution based on n-gram model is proposed. A method of local error detection based on the combined model of 2-gram and 3-gram is proposed, and a method of local error correction based on 3-gram model is proposed. Experiments show that the error detection recall rate is 83.1%, the error detection accuracy rate is 41.5%, the F-score is 55.4%; the error correction rate is 78.1%. The method is compared with the 2-gram model and the 3-gram model. The accuracy of error detection is increased by 7.2% and 8.2% respectively. The F-score is increased by 6.3% and 8.2% respectively.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.