A note on undetected typing errors
Communications of the ACM
Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
A natural language parser with interleaved spelling correction supporting lexical functional grammar and ill-formed input
Combining Trigram-based and feature-based methods for context-sensitive spelling correction
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Categorizing Unknown Words: A Decision Tree-Based Misspelling Identifier
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
ITS Tools for Natural Language Dialogue: A Domain-Independent Parser and Planner
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Non-word identification or spell checking without a dictionary
Journal of the American Society for Information Science and Technology
Compound noun segmentation based on lexical data extracted from corpus
Natural Language Engineering
Plan-based dialogue management in a physics tutor
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Categorizing unknown words: using decision trees to identify names and misspellings
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Compound noun segmentation based on lexical data extracted from corpus
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Artificial Intelligence in Medicine
Effective spelling correction in web queries and run-time DB construction
Proceedings of the 2009 International Conference on Hybrid Information Technology
CIAA'05 Proceedings of the 10th international conference on Implementation and Application of Automata
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This paper describes a spelling correction system that functions as part of an intelligent tutor that carries on a natural language dialogue with its users. The process that searches the lexicon is adaptive as is the system filter, to speed up the process. The basis of our approach is the interaction between the parser and the spelling corrector. Alternative correction targets are fed back to the parser, which does a series of syntactic and semantic checks, based on the dialogue context, the sentence context, and the phrase context.