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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.

REFERENCES

• 1: BLAIR, CHARLES R. A program for correcting spelling errors. Informat. Contr. 3 (March 1960), 60-67.
• 2: Leon Davidson, Retrieval of misspelled names in an airlines passenger record system, Communications of the ACM, v.5 n.3, p.169-171, March 1962 [doi>10.1145/366862.366913]
• 3: Herbert T. Glantz, On the Recognition of Information With a Digital Computer, Journal of the ACM (JACM), v.4 n.2, p.178-188, April 1957 [doi>10.1145/320868.320878]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.1 Office Automation
          Subjects: Word processing

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Dictionaries

  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING

General Terms:
Design, Documentation, Languages, Management, Performance, Reliability, Theory