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In information theory, the Hamming distance between two strings or vectors of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other, or equivalently, the minimum number of errors that could have transformed one string into the other.
It is at least the absolute value of the difference of the sizes of the two strings. It is at most the length of the longer string. It is zero if and only if the strings are equal. If the strings have the same size, the Hamming distance is an upper bound on the Levenshtein distance. The Hamming distance is the number of positions at which the ...
As such, for two objects and having descriptors, the similarity is defined as: = = =, where the are non-negative weights and is the similarity between the two objects regarding their -th variable. In spectral clustering , a similarity, or affinity, measure is used to transform data to overcome difficulties related to lack of convexity in the ...
The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). [2] It operates between two input strings, returning a number equivalent to the number of substitutions and deletions needed in order to transform one input string into another.
In C, the functions strcmp and memcmp perform a three-way comparison between strings and memory buffers, respectively. They return a negative number when the first argument is lexicographically smaller than the second, zero when the arguments are equal, and a positive number otherwise.
Various algorithms exist that solve problems beside the computation of distance between a pair of strings, to solve related types of problems. Hirschberg's algorithm computes the optimal alignment of two strings, where optimality is defined as minimizing edit distance. Approximate string matching can be formulated in terms of edit distance.
A fuzzy Mediawiki search for "angry emoticon" has as a suggested result "andré emotions" In computer science, approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly).
two different references to the same object, e.g., two nicknames for the same person; In many modern programming languages, objects and data structures are accessed through references. In such languages, there becomes a need to test for two different types of equality: Location equality (identity): if two references (A and B) reference the same ...