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  2. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    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.

  3. Gene expression programming - Wikipedia

    en.wikipedia.org/wiki/Gene_expression_programming

    This kind of expression tree consists of the phenotypic expression of GEP genes, whereas the genes are linear strings encoding these complex structures. For this particular example, the linear string corresponds to: 01234567 Q*-+abcd. which is the straightforward reading of the expression tree from top to bottom and from left to right.

  4. Byte pair encoding - Wikipedia

    en.wikipedia.org/wiki/Byte_pair_encoding

    Byte pair encoding [1] [2] (also known as digram coding) [3] is an algorithm, first described in 1994 by Philip Gage, for encoding strings of text into tabular form for use in downstream modeling. [4] A slightly-modified version of the algorithm is used in large language model tokenizers. The original version of the algorithm focused on ...

  5. Feature hashing - Wikipedia

    en.wikipedia.org/wiki/Feature_hashing

    In a typical document classification task, the input to the machine learning algorithm (both during learning and classification) is free text. From this, a bag of words (BOW) representation is constructed: the individual tokens are extracted and counted, and each distinct token in the training set defines a feature (independent variable) of each of the documents in both the training and test sets.

  6. Semi-Thue system - Wikipedia

    en.wikipedia.org/wiki/Semi-Thue_system

    A string rewriting system or semi-Thue system is a tuple (,) where . is an alphabet, usually assumed finite. [5] The elements of the set (* is the Kleene star here) are finite (possibly empty) strings on , sometimes called words in formal languages; we will simply call them strings here.

  7. Burrows–Wheeler transform - Wikipedia

    en.wikipedia.org/wiki/Burrows–Wheeler_transform

    The Burrows–Wheeler transform (BWT, also called block-sorting compression) rearranges a character string into runs of similar characters. This is useful for compression, since it tends to be easy to compress a string that has runs of repeated characters by techniques such as move-to-front transform and run-length encoding.

  8. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Arithmetic coding is a more modern coding technique that uses the mathematical calculations of a finite-state machine to produce a string of encoded bits from a series of input data symbols. It can achieve superior compression compared to other techniques such as the better-known Huffman algorithm.

  9. Shannon–Fano coding - Wikipedia

    en.wikipedia.org/wiki/Shannon–Fano_coding

    The codeword for that symbol is the string of "0"s and "1"s that records which half of the divides it fell on. This method was proposed in a later (in print) technical report by Fano (1949). Shannon–Fano codes are suboptimal in the sense that they do not always achieve the lowest possible expected codeword length, as Huffman coding does. [ 1 ]