Gestalt Pattern Matching, also Ratcliff/Obershelp Pattern Recognition, is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W.

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.

1. A function is defined to take arguments of a particular type, form or value. When applying the function to its actual arguments it is necessary to match the type, form or value of the actual arguments against the formal arguments in some definition. For example, the function length [] = 0 length (x:xs) = 1 + length xs uses pattern matching in its argument to distinguish a null list from a non-null one. There are well known algorithm for translating pattern matching into conditional expressions such as "if" or "case". E.g. the above function could be transformed to length l = case l of [] -> 0 x:xs -> 1 : length xs Pattern matching is usually performed in textual order though there are languages which match more specific patterns before less specific ones. 2. Descriptive of a type of language or utility such as awk or Perl which is suited to searching for strings or patterns in input data, usually using some kind of {regular expression}. (1994-11-28)

In casting, a pattern is a replica of the object to be cast, used to prepare the cavity into which molten material will be poured during the casting process.

In sewing and fashion design, a pattern is the template from which the parts of a garment are traced onto woven or knitted fabrics before being cut out and assembled. Patterns are usually made of paper, and are sometimes made of sturdier materials like paperboard or cardboard if they need to be more robust to withstand repeated use.

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.

In computer programming, the strategy pattern (also known as the policy pattern) is a behavioral software design pattern that enables selecting an algorithm at runtime. Instead of implementing a single algorithm directly, code receives run-time instructions as to which in a family of algorithms to use.

<artificial intelligence, data processing> A branch of artificial intelligence concerned with the classification or description of observations. Pattern recognition aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. A complete pattern recognition system consists of a sensor that gathers the observations to be classified or described; a feature extraction mechanism that computes numeric or symbolic information from the observations; and a classification or description scheme that does the actual job of classifying or describing observations, relying on the extracted features. The classification or description scheme is usually based on the availability of a set of patterns that have already been classified or described. This set of patterns is termed the training set and the resulting learning strategy is characterised as supervised. Learning can also be unsupervised, in the sense that the system is not given an a priori labelling of patterns, instead it establishes the classes itself based on the statistical regularities of the patterns. The classification or description scheme usually uses one of the following approaches: statistical (or {decision theoretic}), syntactic (or structural), or neural. Statistical pattern recognition is based on statistical characterisations of patterns, assuming that the patterns are generated by a probabilistic system. Structural pattern recognition is based on the structural interrelationships of features. Neural pattern recognition employs the neural computing paradigm that has emerged with neural networks. (1995-09-22)

Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.

In software engineering, the adapter pattern is a software design pattern (also known as wrapper, an alternative naming shared with the decorator pattern) that allows the interface of an existing class to be used as another interface. It is often used to make existing classes work with others without modifying their source code.