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The distance (or perpendicular distance) from a point to a line is the shortest distance from a fixed point to any point on a fixed infinite line in Euclidean geometry. It is the length of the line segment which joins the point to the line and is perpendicular to the line. The formula for calculating it can be derived and expressed in several ways.
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.
The Damerau–Levenshtein distance LD(CA, ABC) = 2 because CA → AC → ABC, but the optimal string alignment distance OSA(CA, ABC) = 3 because if the operation CA → AC is used, it is not possible to use AC → ABC because that would require the substring to be edited more than once, which is not allowed in OSA, and therefore the shortest ...
Computing the Levenshtein distance is based on the observation that if we reserve a matrix to hold the Levenshtein distances between all prefixes of the first string and all prefixes of the second, then we can compute the values in the matrix in a dynamic programming fashion, and thus find the distance between the two full strings as the last ...
The closest pair of points problem or closest pair problem is a problem of computational geometry: given points in metric space, find a pair of points with the smallest distance between them. The closest pair problem for points in the Euclidean plane [ 1 ] was among the first geometric problems that were treated at the origins of the systematic ...
Variants of edit distance that are not proper metrics have also been considered in the literature. [1] Other useful properties of unit-cost edit distances include: LCS distance is bounded above by the sum of lengths of a pair of strings. [1]: 37 LCS distance is an upper bound on Levenshtein distance.
The term minimum distance may refer to Minimum distance estimation, a statistical method for fitting a model to data; Closest pair of points problem, the algorithmic problem of finding two points that have the minimum distance among a larger set of points; Euclidean distance, the minimum length of any curve between two points in the plane
The distance from a point to a plane in three-dimensional Euclidean space [8] The distance between two lines in three-dimensional Euclidean space [9] The distance from a point to a curve can be used to define its parallel curve, another curve all of whose points have the same distance to the given curve. [10]