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Some Aspects of Superstring Theory
Published in Harish Parthasarathy, Supersymmetry and Superstring Theory with Engineering Applications, 2023
We usually assume the string metric to be flat, ie ((hαβ))=diag[1,−1]
Some Aspects of Superstring Theory
Published in Harish Parthasarathy, Advanced Probability and Statistics: Applications to Physics and Engineering, 2023
We usually assume the string metric to be flat, ie ((hαβ))=diag[1,−1]
Results and Conclusions
Published in Krzysztof Wołk, Machine Learning in Translation Corpora Processing, 2019
In information theory and computer science, the Levenshtein distance is regarded as a string metric for the measurement of dissimilarity between two sequences. The Levenshtein distance between points or words is the minimum possible number of unique edits to the data (e.g., insertions or deletions) that are required to replace one word with another.
A Levenshtein distance-based method for word segmentation in corpus augmentation of geoscience texts
Published in Annals of GIS, 2023
Jinqu Zhang, Lang Qian, Shu Wang, Yunqiang Zhu, Zhenji Gao, Hailong Yu, Weirong Li
Levenshtein distance, also named edit distance, is proposed by Levenshtein in 1966. it is a string metric for measuring the difference between two words. The Levenshtein distance between two words is the minimum number of operations required to change one word into the other, including insertions, deletions, or substitutions. According to the definition of Levenshtein distance, the fewer editing operations, the higher the similarity between two words. This can be used to determine whether two words are synonyms. The Levenshtein distance between two strings a, b can be calculated by the following equation: