enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. 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.

  4. 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.

  5. Longest repeated substring problem - Wikipedia

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

    In computer science, the longest repeated substring problem is the problem of finding the longest substring of a string that occurs at least twice. This problem can be solved in linear time and space Θ ( n ) {\displaystyle \Theta (n)} by building a suffix tree for the string (with a special end-of-string symbol like '$' appended), and finding ...

  6. 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]

  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. 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.

  9. Substring - Wikipedia

    en.wikipedia.org/wiki/Substring

    A suffix tree for a string is a trie data structure that represents all of its suffixes. Suffix trees have large numbers of applications in string algorithms. The suffix array is a simplified version of this data structure that lists the start positions of the suffixes in alphabetically sorted order; it has many of the same applications.