The DOI matches its Crossref record.
A technique for computer detection and correction of spelling errors
Open accessAbstract
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.
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Cited by
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Martín-Martín, A., Thelwall, M., Orduna-Malea, E., & Delgado López-Cózar, E. (2021) · Scientometrics · doi:10.1007/s11192-020-03690-4 · Cited by 1,018
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Grauman, K., Westbury, A., Byrne, E., Chavis, Z., Furnari, A., Girdhar, R., Hamburger, J., Jiang, H., Liu, M., Liu, X., et al. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01842 · Cited by 630
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PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
Zhu, K., Wang, J., Zhou, J., Wang, Z., Chen, H., Wang, Y., Yang, L., Ye, W., Zhang, Y., Gong, N., et al. (2023) · Proceedings of the 1st ACM Workshop on Large AI Systems and Models with Privacy and Safety Analysis · doi:10.1145/3689217.3690621 · Cited by 151
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Lu, N., Wu, G., Zhang, Z., Zheng, Y., Ren, Y., & Choo, K. R. (2020) · Concurrency and Computation: Practice and Experience · doi:10.1002/cpe.5627 · Cited by 76
Enhancing Levenshtein’s Edit Distance Algorithm for Evaluating Document Similarity
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From Legacy to Standard: LLM-Assisted Transformation of Cybersecurity Playbooks into CACAO Format
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Metadata
- Authors
- Damerau, F. J.
- Venue
- Communications of the ACM
- Published
- 1964-03
- Volume
- 7
- Issue
- 3
- Pages
- 171-176
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2066792529
- Cited by
- 1,575
- References
- 0
- FWCI
- 3.17
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
