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In computer science, a suffix array is a sorted array of all suffixes of a string. It is a data structure used in, among others, full-text indices, data-compression algorithms, and the field of bibliometrics. Suffix arrays were introduced by Manber & Myers (1990) as a simple, space efficient alternative to suffix trees.
In the array, each suffix is represented by an integer pair (,) which denotes the suffix starting from position in . In the case where different strings in have identical suffixes, in the generalized suffix array, those suffixes will occupy consecutive positions. However, for convenience, the exception can be made where repeats will not be listed.
In computer science, Ukkonen's algorithm is a linear-time, online algorithm for constructing suffix trees, proposed by Esko Ukkonen in 1995. [1] The algorithm begins with an implicit suffix tree containing the first character of the string.
Compressed suffix arrays are a general class of data structure that improve on the suffix array. [1] [2] These data structures enable quick search for an arbitrary string with a comparatively small index. Given a text T of n characters from an alphabet Σ, a compressed suffix array supports searching for arbitrary patterns in T.
The suffix array reduces this requirement to a factor of 8 (for array including LCP values built within 32-bit address space and 8-bit characters.) This factor depends on the properties and may reach 2 with usage of 4-byte wide characters (needed to contain any symbol in some UNIX-like systems, see wchar_t ) on 32-bit systems.
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 computer science, the longest common prefix array (LCP array) is an auxiliary data structure to the suffix array.It stores the lengths of the longest common prefixes (LCPs) between all pairs of consecutive suffixes in a sorted suffix array.
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.