The DOI matches its Crossref record.
The String-to-String Correction Problem
Open accessAbstract
The string-to-string correction problem is to determine the distance between two strings as measured by the minimum cost sequence of “edit operations” needed to change the one string into the other. The edit operations investigated allow changing one symbol of a string into another single symbol, deleting one symbol from a string, or inserting a single symbol into a string. An algorithm is presented which solves this problem in time proportional to the product of the lengths of the two strings. Possible applications are to the problems of automatic spelling correction and determining the longest subsequence of characters common to two strings.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Normalized Levenshtein Distance Metric
Yujian, L., & Bo, L. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1078 · Cited by 986
A survey on tree edit distance and related problems
Bille, P. (2005) · Theoretical Computer Science · doi:10.1016/j.tcs.2004.12.030 · Cited by 751
Hall, P. A. V., & Dowling, G. R. (1980) · ACM Computing Surveys · doi:10.1145/356827.356830 · Cited by 586
Information retrieval and text mining technologies for chemistry
Krallinger, M., Rabal, O., Lourenço, A., Oyarzabal, J., & Valencia, A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00851 · Cited by 281
Analyzing the input stream for character- level errors in unconstrained text entry evaluations
Wobbrock, J. O., & Myers, B. A. (2006) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1188816.1188819 · Cited by 200
Metadata
- Authors
- Wagner, R. A., & Fischer, M. J.
- Venue
- Journal of the ACM
- Published
- 1974-01
- Volume
- 21
- Issue
- 1
- Pages
- 168-173
- ISSN
- 0004-5411 (ISSN-L)
- 1557-735X
- OpenAlex
- W1970026646
- Cited by
- 3,032
- References
- 0
- FWCI
- 15.05
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The String-to-String Correction Problem. https://app.cochat.ai/papers/10.1145/321796.321811
- The paper
- Wagner, R. A., & Fischer, M. J. (1974). The String-to-String Correction Problem. Journal of the ACM. https://doi.org/10.1145/321796.321811
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
