Search results
Results from the WOW.Com Content Network
Has two implementations, with PCRE being the more efficient in speed, functions POSIX C POSIX.1 web publication: Licensed by the respective implementation Supports POSIX BRE and ERE syntax Python: python.org: Python Software Foundation License: Python has two major implementations, the built in re and the regex library. Ruby: ruby-doc.org
The longest common substrings of a set of strings can be found by building a generalized suffix tree for the strings, and then finding the deepest internal nodes which have leaf nodes from all the strings in the subtree below it. The figure on the right is the suffix tree for the strings "ABAB", "BABA" and "ABBA", padded with unique string ...
More generally, an equation E=F between regular-expression terms with variables holds if, and only if, its instantiation with different variables replaced by different symbol constants holds. [30] [31] Every regular expression can be written solely in terms of the Kleene star and set unions over finite words. This is a surprisingly difficult ...
The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]
Computing E(m, j) is very similar to computing the edit distance between two strings. In fact, we can use the Levenshtein distance computing algorithm for E ( m , j ), the only difference being that we must initialize the first row with zeros, and save the path of computation, that is, whether we used E ( i − 1, j ), E( i , j − 1) or E ( i ...
In formal language theory and pattern matching (including regular expressions), the concatenation operation on strings is generalised to an operation on sets of strings as follows: For two sets of strings S 1 and S 2, the concatenation S 1 S 2 consists of all strings of the form vw where v is a string from S 1 and w is a string from S 2, or ...
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.
The difference between the two algorithms consists in that the optimal string alignment algorithm computes the number of edit operations needed to make the strings equal under the condition that no substring is edited more than once, whereas the second one presents no such restriction. Take for example the edit distance between CA and ABC.