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  2. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    In order to find the number of occurrences of a given string (length ) in a text (length ), [3] We use binary search against the suffix array of T {\displaystyle T} to find the starting and end position of all occurrences of P {\displaystyle P} .

  3. Longest repeated substring problem - Wikipedia

    en.wikipedia.org/wiki/Longest_repeated_substring...

    The string spelled by the edges from the root to such a node is a longest repeated substring. The problem of finding the longest substring with at least k {\displaystyle k} occurrences can be solved by first preprocessing the tree to count the number of leaf descendants for each internal node, and then finding the deepest node with at least k ...

  4. 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.

  5. Knuth–Morris–Pratt algorithm - Wikipedia

    en.wikipedia.org/wiki/Knuth–Morris–Pratt...

    In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.

  6. Boyer–Moore string-search algorithm - Wikipedia

    en.wikipedia.org/wiki/Boyer–Moore_string-search...

    The Boyer–Moore algorithm searches for occurrences of P in T by performing explicit character comparisons at different alignments. Instead of a brute-force search of all alignments (of which there are ⁠ n − m + 1 {\displaystyle n-m+1} ⁠ ), Boyer–Moore uses information gained by preprocessing P to skip as many alignments as possible.

  7. Substring - Wikipedia

    en.wikipedia.org/wiki/Substring

    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. In the mathematical literature, substrings are also called subwords (in America) or factors (in Europe).

  8. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The picture shows two strings where the problem has multiple solutions. Although the substring occurrences always overlap, it is impossible to obtain a longer common substring by "uniting" them. The strings "ABABC", "BABCA" and "ABCBA" have only one longest common substring, viz. "ABC" of length 3.

  9. Frequent subtree mining - Wikipedia

    en.wikipedia.org/wiki/Frequent_subtree_mining

    Starting from the root of the tree, node labels are added to the string in depth-first search order. -1 is added to the string whenever the search process backtracks from a child to its parent. For example, a simple binary tree with root labelled A, a left child labelled B and right child labelled C can be represented by a string A B -1 C -1.