Automated methods for correcting errors in grammar and usage

Over the last several decades, the number of electronic documents has increased dramatically. With the growing availability of computers, more and more people are using text editors. However, the development of automated methods for correcting mistakes in text has not progressed as far. Text editors usually employ basic spell checking techniques and address very few mistakes of other types. In this thesis, we propose two methods for correcting errors in grammar and usage. First, we propose a novel approach to the problem of training classifiers to detect and correct errors in text by selectively introducing mistakes into the training data and show that this method is superior to the traditional method of training using clean data. Second, we define high-level features and propose a method of correcting mistakes using these features. We combine the two methods and build a system for correcting mistakes in article usage made by non-native speakers of English.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Rozovskaya, Alla

Contributors dc:contributor

• Roth, Dan

• Text correction
• Correcting ESL mistakes
• Errors in article usage
• automated methods for correcting ESL mistakes
• annotated ESL corpus
• Error statistics
• Features for article correction
• English as a Second Language (ESL)

Statement dc:rights

• Copyright 2010 Alla Rozovskaya

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/15967

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/15967