Search results
Results From The WOW.Com Content Network
It should only contain pages that are Pattern matching programming languages or lists of Pattern matching programming languages, as well as subcategories containing those things (themselves set categories). Topics about Pattern matching programming languages in general should be placed in relevant topic categories.
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.
In computer science, compressed pattern matching (abbreviated as CPM) is the process of searching for patterns in compressed data with little or no decompression. Searching in a compressed string is faster than searching an uncompressed string and requires less space.
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.
Download as PDF; Printable version; In other projects Wikimedia Commons; ... Pattern matching programming languages (2 C, 30 P) R. Regular expressions (1 C, 12 P) S.
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
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. It is used to determine ...
Low power consumption is useful for datacentre equipment. Predictable runtime. Better price/performance than software sliding window aligners on current hardware, but not better than software BWT-based aligners currently. Can manage large numbers (>2) of mismatches. Will find all hit positions for all seeds.