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  2. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The variable z is used to hold the length of the longest common substring found so far. The set ret is used to hold the set of strings which are of length z. The set ret can be saved efficiently by just storing the index i, which is the last character of the longest common substring (of size z) instead of S[(i-z+1)..i].

  3. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    A longest common subsequence (LCS) is the longest subsequence common to all sequences in a set of sequences (often just two sequences). It differs from the longest common substring : unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences.

  4. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]

  5. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    Longest common subsequence (LCS) distance is edit distance with insertion and deletion as the only two edit operations, both at unit cost. [1]: 37 Similarly, by only allowing substitutions (again at unit cost), Hamming distance is obtained; this must be restricted to equal-length strings. [1]

  6. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.

  7. Chvátal–Sankoff constants - Wikipedia

    en.wikipedia.org/wiki/Chvátal–Sankoff_constants

    Compute a longest common subsequence of these two strings, and let , be the random variable whose value is the length of this subsequence. Then the expected value of λ n , k {\displaystyle \lambda _{n,k}} is (up to lower-order terms) proportional to n , and the k th Chvátal–Sankoff constant γ k {\displaystyle \gamma _{k}} is the constant ...

  8. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    It stores the lengths of the longest common prefixes (LCPs) between all pairs of consecutive suffixes in a sorted suffix array. For example, if A := [ aab , ab , abaab , b , baab ] is a suffix array, the longest common prefix between A [1] = aab and A [2] = ab is a which has length 1, so H [2] = 1 in the LCP array H .

  9. Substring - Wikipedia

    en.wikipedia.org/wiki/Substring

    If is a substring of , it is also a subsequence, which is a more general concept. The occurrences of a given pattern in a given string can be found with a string searching algorithm. Finding the longest string which is equal to a substring of two or more strings is known as the longest common substring problem.