A partial dictionary of English in computer-usable form
Literary & Linguistic Computing
Spelling checkers,spelling correctors and the misspellings of poor spellers
Information Processing and Management: an International Journal
Context based spelling correction
Information Processing and Management: an International Journal
Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Winnow-Based Approach to Context-Sensitive Spelling Correction
Machine Learning - Special issue on natural language learning
The String-to-String Correction Problem
Journal of the ACM (JACM)
Automatic spelling correction in scientific and scholarly text
Communications of the ACM
Computer programs for detecting and correcting spelling errors
Communications of the ACM
A technique for computer detection and correction of spelling errors
Communications of the ACM
Retrieval of misspelled names in an airlines passenger record system
Communications of the ACM
Scaling Up Context-Sensitive Text Correction
Proceedings of the Thirteenth Conference on Innovative Applications of Artificial Intelligence Conference
CIAA '01 Revised Papers from the 6th International Conference on Implementation and Application of Automata
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
Correcting real-word spelling errors by restoring lexical cohesion
Natural Language Engineering
Pronunciation modeling for improved spelling correction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Fast Approximate Search in Large Dictionaries
Computational Linguistics
Managing misspelled queries in IR applications
Information Processing and Management: an International Journal
On using context for automatic correction of non-word misspellings in student essays
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
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Having located a misspelling, a spellchecker generally offers some suggestions for the intended word. Even without using context, a spellchecker can draw on various types of information in ordering its suggestions. A series of experiments is described, beginning with a basic corrector that implements a well-known algorithm for reversing single simple errors, and making successive enhancements to take account of substring matches, pronunciation, known error patterns, syllable structure and word frequency. The improvement in the ordering produced by each enhancement is measured on a large corpus of misspellings. The final version is tested on other corpora against a widely used commercial spellchecker and a research prototype.