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A naive implementation would compute the largest common subsequence of all the strings in the set in (). [ 6 ] A generalized suffix array can be utilized to find the longest previous factor array, a concept central to text compression techniques and in the detection of motifs and repeats [ 7 ]
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.
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 ...
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} .
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.
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.
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 ...
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. The figure on the right is the suffix tree for the strings "ABAB", "BABA" and "ABBA", padded with unique string ...