
	Where results make sense

Topic: Levenshtein distance

Related Topics

Edit distance

Hamming distance

Distance

Mahalanobis distance

Timeline of algorithms

Coding theory

Information theory

Jabberwocky

Brillig

List of filter terms

Bandersnatch

Peugeot

Federal Standard 1037C

The Annotated Alice

In the News (Sat 5 Dec 09)

Northern Trust

Marvin Harrison

Peter Chernin

Gary Locke

Match Play

Penelope Cruz

Mickey Rourke

AR Rahman

Danny Boyle

Hugh Jackman

	NationMaster - Encyclopedia: Levenshtein distance
		The Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character.
		In computer science, Levenshtein automata are a family of finite state automata that can recognize the set V of all words in a formal language for which the Levenshtein distance to an arbitrary word W does not exceed a particular constant.
		In information theory and computer science, the Levenshtein distance or edit distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character.
	www.nationmaster.com /encyclopedia/Levenshtein-distance (1872 words)

	Levenshtein distance
		In information theory, the Levenshtein distance or edit distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution.
		The Levenshtein distance has several simple upper and lower bounds that are useful in applications which compute many of them and compare them.
		If the strings are the same size, the Hamming distance is an upper bound on the Levenshtein distance; otherwise the Hamming distance plus the difference in sizes is an upper bound.
	www.xasa.com /wiki/en/wikipedia/l/le/levenshtein_distance.html (673 words)

	Levenshtein algorithm
		Levenshtein distance is obtained by finding the cheapest way to transform one string into another.
		The direct results of the application of the Levenshtein algorithm is the distance calculated between the strings and the set of transformations that contributed to the least costly set responsible for that distance.
		Wilbert Heeringa's dialectology project uses Levenshtein distance to estimate the proximity of dialect pronunciations.
	odur.let.rug.nl /~kleiweg/lev/levenshtein.html (603 words)

	[No title]
		Levenshtein distance (LD) is a measure of the similarity between two inputs, which we will refer to as the
		The Damerau distance is almost identical to the Levenshtein distance but can tolerate adjascent charac- ters that have been swapped, a common spelling mistake or typographic error.
		The Levenshtein distance algorithm assumes that the cost of all insertions or conversions is equal.
	monkey.org /~jose/software/libdistance/test.html (1003 words)

	Levenshtein distance as a useful pattern matching algorithm to decipher scrabble spam (Site not responding. Last check: )
		Enter Levenshtein Distance algorithm: " Levenshtein distance (LD) is a measure of the similarity between two strings, which we will refer to as the source string (s) and the target string (t).
		The distance is the number of deletions, insertions, or substitutions required to transform s into t.
		Levenshtein distance is named after the Russian scientist Vladimir Levenshtein, who devised the algorithm in 1965.
	www.bogofilter.org /pipermail/bogofilter/2005-February/007621.html (323 words)

	Levenshtein distance - Education - Information - Educational Resources - Encyclopedia - Music
		For example, the Levenshtein distance between "kitten" and "sitting" is 3, since these three edits change one into the other, and there is no way to do it with less than three edits:
		There are also further generalizations of the Levenshtein distance that consider, for example, exchanging two characters as an operation.
		CSE 590BI, Winter 1996 Algorithms in Molecular Biology The algorithms from lectures 2, 3 and 4 are based on the Levenshtein distance but implement a different scoring function.
	www.music.us /education/L/Levenshtein-distance.htm (862 words)

	Class: Amatch::Levenshtein
		The Levenshtein edit distance is defined as the minimal costs involved to transform one string into another by using three elementary operations: deletion, insertion and substitution of a character.
		The edit distance between "wine" and "wine" is 0 of course: no operation is necessary for the transformation — they’re already the same string.
		Levenshtein distance metric number between 0.0 for very unsimilar strings and 1.0 for an exact match.
	amatch.rubyforge.org /doc/classes/Amatch/Levenshtein.html (234 words)

	Reference.com/Encyclopedia/Levenshtein distance
		The Levenshtein distance between two strings is given by the minimum number of operations needed to transform one string into the other, where an operation is an insertion, deletion, or substitution of a single character.
		There are also further generalizations of the Levenshtein distance that consider, for example, exchanging two characters as an operation, like in the Damerau-Levenshtein distance algorithm.
		Levenshtein distance library function in PHP - Since PHP 3.0.17, there is a built-in levenshtein function.
	www.reference.com /browse/wiki/Levenshtein_distance (798 words)

	String Similarity Metrics for Information Integration
		There are many extensions to the Levenshtein distance function typically these alter the d(i,j) function, but further extensions can be made for instance, the Needleman-Wunch distance for which Levenshtein is equivalent if the gap distance is 1.
		Again similar to the to Levenshtein distance, this was developed to identify optimal allignments between related DNA and protein sequencies.
		This distance is often incorrectly reffered to as an implementation of the Smith-Waterman distance approach.
	www.dcs.shef.ac.uk /~sam/stringmetrics.html (3865 words)

	Distance Summary
		One might attempt to define the distance between two non-empty subsets of a given set as the infimum of the distances between any two of their respective points, which would agree with the every-day use of the word.
		Distance is a scalar quantity, containing only a magnitude, whereas displacement is an equivalent vector quantity containing both magnitude and direction.
		The distance covered by a vehicle (often recorded by an odometer), person, animal, object, etc. should be distinguished from the distance from starting point to end point, even if latter is taken to mean e.g.
	www.bookrags.com /Distance (3719 words)

	Levenshtein Distance - Dedupe
		The Levenshtein distance is defined as the minimal number of characters you have to replace, insert or delete to transform str1 into str2.
		Damerau-Levenshtein distance is an extension of Levenshtein distance that counts transposition as a single edit operation.
		Strictly speaking, the Damerau-Levenshtein distance is equal to the minimal number of insertions, deletions, substitutions and transpositions needed to transform one string into the other.
	tickett.net /dedupe/index.php/Levenshtein_Distance (390 words)

	Levenshtein distance
		(2) A Θ(m × n) algorithm to compute the distance between strings, where m and n are the lengths of the strings.
		Levenshtein distance (Java, C++, Visual Basic), includes a great explanation and links to code in Perl, C, JavaScript, Python, and many more languages.
		March 2003 pictures of Levenshtein at a reception.
	www.nist.gov /dads/HTML/Levenshtein.html (228 words)

	Efficient Implementation of the Levenshtein-Algorithm, Fault-tolerant Search Technology, Error-tolerant Search ...
		The Levenshtein algorithm (also called Edit-Distance) calculates the least number of edit operations that are necessary to modify one string to obtain another string.
		A matrix is initialized measuring in the (m,n)-cell the Levenshtein distance between the m-character prefix of one with the n-prefix of the other word.
		This way the number in the lower right corner is the Levenshtein distance between both words.
	www.levenshtein.net (223 words)

	Levenshtein algorithm
		It fills out the rest of the array while finding all the distances between each initial prefix of the source on the one hand and each initial prefix of the target.
		Each [i,j] cell represents the (minimal) distance between the first i letters of the source word and the first j letters of the target.
		It is used in some spell checkers to guess at which word (from a dictionary) is meant when an unknown word is encountered.
	www.let.rug.nl /~kleiweg/lev/levenshtein.html (603 words)

	Levenshtein (Site not responding. Last check: )
		Levenshtein is a C extension module for Python and a C library (or strives to be).
		The possibility to use Levenshtein as a plain C library is more-or-less theoretical for the present.
		Levenshtein is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
	trific.ath.cx /resources/python/levenshtein (319 words)

	Levenshtein distance
		Strictly speaking, the Damerau-Levenshtein distance is equal to the minimal number of insertions, deletions, substitutions and transpositions needed to transform one string into the other.
		However, one must remember that restricted edit distance does not always satisfy triangle inequality and, thus, cannot be used with metric trees.
		In contrast to n-gram distance, Levenshtein distance is a de-facto standard similarity function.
	www.libraryoflibrary.com /E_n_c_p_d_Levenshtein_distance.html (4153 words)

	Dr. Dobb's \| Finding String Distances \| July 22, 2001
		This says that the distance from point A to point C cannot be less than the distance from A to B added to the distance from B to C. In the case of travel, it cannot be shorter to go from San Francisco to Los Angeles by way of Memphis (unless you use Federal Express).
		Other related constraints are: Distance cannot be negative, the distance between two identical strings is zero, and the distance between two strings is the same in either direction (known as the "reflexivity property").
		The procedure calculate_matrix() fills the cells in M with the minimum edit distances at each stage of the transformation from string A to B. The characters in string A lie along the vertical axis of M at column 0, while those in string B lie on the horizontal axis at row 0.
	www.ddj.com /dept/architect/184408746?pgno=2 (2832 words)

	Dynamic Programming Algorithm, Edit Distance
		The edit distance of two strings, s1 and s2, is defined as the minimum number of point mutations required to change s1 into s2, where a point mutation is one of:
		If only the value of the edit distance is needed, only two rows of the matrix need be allocated; they can be "recycled", and the space complexity is then O(s1), i.e.
		Modify the edit distance DPA to that it treats a transposition as a single point-mutation.
	www.csse.monash.edu.au /~lloyd/tildeAlgDS/Dynamic/Edit (1208 words)

	Fuzzy (approximate) searching FAQ, how to search
		The edit distance is often referred to as a Levenshtein distance.
		One must note, however, that with Levenshtein distance an elementary operation is a single character insertion, deletion or substitution.
		The distance between strings equals to the minimal possible weight (or cost) among the sequences that transform one string into another.
	itman.narod.ru /english/ir/faq/fzfaq_search.html (1076 words)

	String::Levenshtein (Site not responding. Last check: )
		The Levenshtein distance is defined as the minimum number of characters that must be added, removed, or changed in order to transform one string into another.
		Returns the smallest number of characters that must be added, removed or changed in order to transform the shorter of $string1 and $string2 into a prefix of the longer.
		Levenshtein prefix String1 String2 distance distance 0 0 abc 3 0 xyz 3 0 abc abc 0 0 abc xyz 3 3 abc abd 1 1 gumbo gambol 2 1 aaaa bbbbbbb 7 4 McDougall MacDougal 2 2 Smith Smithson 3 0 Smithson Smith 3 0
	world.std.com /~swmcd/steven/perl/lib/String/Levenshtein/Levenshtein.html (167 words)

	Levenshtein distance
		We can adapt the algorithm to use less space, O(m) instead of O(mn), since it only requires that the previous row and current row be stored at any one time.
		Levenshtein Distance, in Three Flavors, by Michael Gilleland (http://www.merriampark.com/ld.htm)
		CSE 590BI, Winter 1996 Algorithms in Molecular Biology (http://www.cs.washington.edu/education/courses/590bi/96wi/) The algorithms from lectures 2, 3 and 4 are based on the Levenshtein distance but implement a different scoring function.
	www.askfactmaster.com /Levenshtein_distance (533 words)

	/devel » Speeding up Levenshtein (written on November 10, 2006 by Marko Samastur)
		Average time to calculate distance between randomly chosen title and rest of them is 9.4 seconds, which is far too much to be useful.
		Since minimum distance is at least as much as a difference in length of both strings, there’s no point in calculating it when difference already exceeds a limit we chose.
		Since Levenshtein’s distance is at least as much as difference between length of two strings, we can start with two strings that have approximately the same length of n.
	markos.gaivo.net /blog/?p=211 (1254 words)

	PHP levenshtein() Function
		The levenshtein() function returns the Levenshtein distance between two strings.
		The Levenshtein distance is the number of characters you have to replace, insert or delete to transform string1 into string2.
		Note: The levenshtein() function is faster than the similar_text() function.
	www.w3schools.com /php/func_string_levenshtein.asp (187 words)

	Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison
		The book is the first, and still best compilation of papers explaining how to measure distance between sequences, and how to compute that measure effectively.
		One may interpret the distance between molecular sequences in terms of the mutations necessary for one molecule to evolve into another.
		In dialectology Levenshtein distance allows analysis of the learned variation in pronunication, its cultural component.
	csli-publications.stanford.edu /site/1575862174.html (322 words)

	Code Library - A C++ implementation of the Levenshtein Distance
		The "Levenshtein distance" is a measure of the similarity between two strings, this algorithm is also refered to as "edit distance".
		The "Levenshtein distance" was named after the russian scientist "Vladimir Levenshtein", who has discovered it back in 1965.
		The smaller the distance between two strings, the closer are those strings syntacticaly.
	code.filehungry.com /product/languages/c___c__/strings/a_c___implementation_of_the_levenshtein_distance (187 words)

	mogul:/lager/levenshtein
		The edit distance is defined as the number of deletions, insertions, or substitutions required to transform the source into the target.
		The greater the distance, the more different the strings are, and vice versa.
		They are both straightforward implementations of Levenshtein's algorithm - a dynamic programming algorithm capable of calculating the edit distance in time proportional to the length of the source times the length of the target.
	www.mozart-oz.org /mogul/info/lager/levenshtein.html (163 words)

Try your search on: Qwika (all wikis)