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In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be a match." The patterns generally have the form of either sequences or tree structures.
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.
This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors.
String matching algorithms (1 C, 16 P) Pages in category "Pattern matching" The following 28 pages are in this category, out of 28 total.
The Commentz-Walter algorithm combines two known algorithms in order to attempt to better address the multi-pattern matching problem. These two algorithms are the Boyer-Moore, which addresses single pattern matching using filtering, and the Aho-Corasick. To do this, the algorithm implements a suffix automaton to search through patterns within ...
In computer science, the Krauss wildcard-matching algorithm is a pattern matching algorithm. Based on the wildcard syntax in common use, e.g. in the Microsoft Windows command-line interface, the algorithm provides a non-recursive mechanism for matching patterns in software applications, based on syntax simpler than that typically offered by regular expressions.
The Rete algorithm (/ ˈ r iː t iː / REE-tee, / ˈ r eɪ t iː / RAY-tee, rarely / ˈ r iː t / REET, / r ɛ ˈ t eɪ / reh-TAY) is a pattern matching algorithm for implementing rule-based systems. The algorithm was developed to efficiently apply many rules or patterns to many objects, or facts , in a knowledge base .
Generalizations of the same idea can be used to find more than one match of a single pattern, or to find matches for more than one pattern. To find a single match of a single pattern, the expected time of the algorithm is linear in the combined length of the pattern and text, although its worst-case time complexity is the product of the two ...