The method described assumes that a word which cannot be found in a dictionary has at most one error, which might be a wrong, missing or extra letter or a single transposition. The unidentified input word is compared to the dictionary again, testing each time to see if the words match—assuming one of these errors occurred. During a test run on garbled text, correct identifications were made for over 95 percent of these error types.

@article{damerau1964technique, author = {Damerau, Fred J.}, title = {A Technique for Computer Detection and Correction of Spelling Errors}, journal = {Commun. ACM}, publisher = {ACM}, address = {New York, NY, USA}, year = {1964}, volume = {7}, number = {3}, pages = {171--176}, url = {http://doi.acm.org/10.1145/363958.363994}, doi = {10.1145/363958.363994}, issn = {0001-0782}, keywords = {damerau, distance, levenshtein, spelling}, abstract = {The method described assumes that a word which cannot be found in a dictionary has at most one error, which might be a wrong, missing or extra letter or a single transposition. The unidentified input word is compared to the dictionary again, testing each time to see if the words match—assuming one of these errors occurred. During a test run on garbled text, correct identifications were made for over 95 percent of these error types.} }

%0 = article %A = Damerau, Fred J. %C = New York, NY, USA %D = 1964 %I = ACM %T = A Technique for Computer Detection and Correction of Spelling Errors %U = http://doi.acm.org/10.1145/363958.363994