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Techniques for automatically correcting words in text

Open access
Kukich, Karen·1992·ACM Computing Surveys

Abstract

Research aimed at correcting words in text has focused on three progressively more difficult problems:(1) nonword error detection; (2) isolated-word error correction; and (3) context-dependent work correction. In response to the first problem, efficient pattern-matching and n -gram analysis techniques have been developed for detecting strings that do not appear in a given word list. In response to the second problem, a variety of general and application-specific spelling correction techniques have been developed. Some of them were based on detailed studies of spelling error patterns. In response to the third problem, a few experiments using natural-language-processing tools or statistical-language models have been carried out. This article surveys documented findings on spelling error patterns, provides descriptions of various nonword detection and isolated-word error correction techniques, reviews the state of the art of context-dependent word correction techniques, and discusses research issues related to all three areas of automatic error correction in text.

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Metadata

Authors
Kukich, K.
Venue
ACM Computing Surveys
Published
1992-12
Volume
24
Issue
4
Pages
377-439
ISSN
  • 0360-0300 (ISSN-L)
  • 1557-7341
OpenAlex
W2010595692
Cited by
1,257
References
2
FWCI
10.28
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Techniques for automatically correcting words in text. https://app.cochat.ai/papers/10.1145/146370.146380
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Kukich, K. (1992). Techniques for automatically correcting words in text. ACM Computing Surveys. https://doi.org/10.1145/146370.146380

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