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  2. Suffix tree - Wikipedia

    en.wikipedia.org/wiki/Suffix_tree

    The worst-case space usage of a suffix tree is seen with a fibonacci word, giving the full nodes. An important choice when making a suffix tree implementation is the parent-child relationships between nodes. The most common is using linked lists called sibling lists. Each node has a pointer to its first child, and to the next node in the child ...

  3. Generalized suffix tree - Wikipedia

    en.wikipedia.org/wiki/Generalized_suffix_tree

    An alternative to building a generalized suffix tree is to concatenate the strings, and build a regular suffix tree or suffix array for the resulting string. When hits are evaluated after a search, global positions are mapped into documents and local positions with some algorithm and/or data structure, such as a binary search in the starting ...

  4. Ukkonen's algorithm - Wikipedia

    en.wikipedia.org/wiki/Ukkonen's_algorithm

    You can find the following characteristics in a suffix tree that uses Ukkonen's algorithm: Implicit suffix tree T i+1 is built on top of implicit suffix tree T i. At any given time, Ukkonen's algorithm builds the suffix tree for the characters seen so far and so it has on-line property, allowing the algorithm to have an execution time of O(n).

  5. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    Generalized suffix tree for the strings "ABAB", "BABA" and "ABBA", numbered 0, 1 and 2. The longest common substrings of a set of strings can be found by building a generalized suffix tree for the strings, and then finding the deepest internal nodes which have leaf nodes from all the strings in the subtree below it.

  6. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    Tries support various operations: insertion, deletion, and lookup of a string key. Tries are composed of nodes that contain links, which either point to other suffix child nodes or null. As for every tree, each node but the root is pointed to by only one other node, called its parent.

  7. Longest repeated substring problem - Wikipedia

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

    This problem can be solved in linear time and space () by building a suffix tree for the string (with a special end-of-string symbol like '$' appended), and finding the deepest internal node in the tree with more than one child. Depth is measured by the number of characters traversed from the root.

  8. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    Given the suffix array and the LCP array of a string =,, … $ of length +, its suffix tree can be constructed in () time based on the following idea: Start with the partial suffix tree for the lexicographically smallest suffix and repeatedly insert the other suffixes in the order given by the suffix array.

  9. Suffix automaton - Wikipedia

    en.wikipedia.org/wiki/Suffix_automaton

    In terms of suffix trees it corresponds to the insertion of the new longest suffix into the suffix tree of . At most two new vertices may be formed after this insertion: one of them corresponding to x ω R {\displaystyle x\omega ^{R}} , while the other one corresponds to its direct ancestor if there was a branching.