The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Algorithms for the Longest Common Subsequence Problem
Open accessAbstract
AaS~ACT Two algorithms are presented that solve the longest common subsequence problem The first algorithm is applicable in the general case and requires O(pn + n log n) time where p is the length of the longest common subsequence The second algorithm requires time bounded by O(p(m + 1 -p)log n) In the common speoal case where p is close to m, this algorithm takes much less time than n ~
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Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
Cited by
Bagnall, A., Lines, J., Bostrom, A., Large, J., & Keogh, E. (2017) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-016-0483-9 · Cited by 1,377
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Ahmed, T., Ghosh, S., Bansal, C., Zimmermann, T., Zhang, X., & Rajmohan, S. (2023) · 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) · doi:10.1109/icse48619.2023.00149 · Cited by 148
The Error Probability of Maximum-Likelihood Decoding over Two Deletion/Insertion Channels
Sabary, O., Yaakobi, E., & Yucovich, A. (2020) · 2020 IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit44484.2020.9174488 · Cited by 10
Metadata
- Authors
- Hirschberg, D. S.
- Venue
- Journal of the ACM
- Published
- 1977-10
- Volume
- 24
- Issue
- 4
- Pages
- 664-675
- ISSN
- 0004-5411 (ISSN-L)
- 1557-735X
- OpenAlex
- W2162744351
- Cited by
- 750
- References
- 1
- FWCI
- 3.38
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Algorithms for the Longest Common Subsequence Problem. https://app.cochat.ai/papers/10.1145/322033.322044
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- Hirschberg, D. S. (1977). Algorithms for the Longest Common Subsequence Problem. Journal of the ACM. https://doi.org/10.1145/322033.322044
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
