Search results
Results from the WOW.Com Content Network
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
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.
This entire process is reflected in reading as well. First, a child recognizes patterns of individual letters, then words, then groups of words together, then paragraphs, and finally entire chapters in books. [25] Learning to read and learning to speak a language are based on the "stepwise refinement of patterns" [25] in perceptual pattern ...
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.
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.
The AIML pattern syntax is a very simple pattern language, substantially less complex than regular expressions and as such less than level 3 in the Chomsky hierarchy. To compensate for the simple pattern matching capabilities, AIML interpreters can provide preprocessing functions to expand abbreviations, remove misspellings, etc.
Learning algorithms for neural networks use local search to choose the weights that will get the right output for each input during training. The most common training technique is the backpropagation algorithm. [105] Neural networks learn to model complex relationships between inputs and outputs and find patterns in data. In theory, a neural ...
New word recognition capabilities have made computer-based learning programs more effective and reliable. [8] Improved technology has enabled eye-tracking, which monitors individuals' saccadic eye movements while they read. This has furthered understanding of how certain patterns of eye movement increases word recognition and processing.