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  2. 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.

  3. Suffix array - Wikipedia

    en.wikipedia.org/wiki/Suffix_array

    Prefix doubling algorithms are based on a strategy of Karp, Miller & Rosenberg (1972). The idea is to find prefixes that honor the lexicographic ordering of suffixes. The assessed prefix length doubles in each iteration of the algorithm until a prefix is unique and provides the rank of the associated suffix.

  4. Longest prefix match - Wikipedia

    en.wikipedia.org/wiki/Longest_prefix_match

    Longest prefix match (also called Maximum prefix length match) refers to an algorithm used by routers in Internet Protocol (IP) networking to select an entry from a routing table. [1] Because each entry in a forwarding table may specify a sub-network, one destination address may match more than one forwarding table entry. The most specific of ...

  5. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    This algorithm runs in () time. The array L stores the length of the longest common suffix of the prefixes S[1..i] and T[1..j] which end at position i and j, respectively. The variable z is used to hold the length of the longest common substring found so far.

  6. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    The prefix S n of S is defined as the first n characters of S. [5] For example, the prefixes of S = (AGCA) are S 0 = S 1 = (A) S 2 = (AG) S 3 = (AGC) S 4 = (AGCA). Let LCS(X, Y) be a function that computes a longest subsequence common to X and Y. Such a function has two interesting properties.

  7. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    Trie data structures are commonly used in predictive text or autocomplete dictionaries, and approximate matching algorithms. [11] Tries enable faster searches, occupy less space, especially when the set contains large number of short strings, thus used in spell checking, hyphenation applications and longest prefix match algorithms.

  8. Ukkonen's algorithm - Wikipedia

    en.wikipedia.org/wiki/Ukkonen's_algorithm

    This order addition of characters gives Ukkonen's algorithm its "on-line" property. The original algorithm presented by Peter Weiner proceeded backward from the last character to the first one from the shortest to the longest suffix. [2] A simpler algorithm was found by Edward M. McCreight, going from the longest to the shortest suffix. [3]

  9. Suffix automaton - Wikipedia

    en.wikipedia.org/wiki/Suffix_automaton

    Anselm Blumer with a drawing of generalized CDAWG for strings ababc and abcab. The concept of suffix automaton was introduced in 1983 [1] by a group of scientists from University of Denver and University of Colorado Boulder consisting of Anselm Blumer, Janet Blumer, Andrzej Ehrenfeucht, David Haussler and Ross McConnell, although similar concepts had earlier been studied alongside suffix trees ...