Linear Time Online Algorithms for Constructing Linear-size Suffix Trie
Diptarama Hendrian, Takuya Takagi, Shunsuke Inenaga, Keisuke Goto,, Mitsuru Funakoshi

TL;DR
This paper introduces two efficient online algorithms for constructing linear-size suffix tries (LSTs) directly from text, eliminating the need to store the input string and matching the efficiency of suffix trees.
Contribution
The paper presents the first online algorithms for directly constructing LSTs from either end of the input string without intermediate suffix tree construction.
Findings
Both algorithms operate in O(n log σ) time and O(n) space.
They do not require storing the input string during construction.
The algorithms work from right-to-left and left-to-right, respectively.
Abstract
The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a text string of length has nodes and edges, and the string label of each edge is encoded by a pair of positions in . Thus, even after the tree is built, the input string needs to be kept stored and random access to is still needed. The \emph{linear-size suffix tries} (\emph{LSTs}), proposed by Crochemore et al. [Linear-size suffix tries, TCS 638:171-178, 2016], are a "stand-alone" alternative to the suffix trees. Namely, the LST of an input text string of length occupies total space, and supports pattern matching and other tasks with the same efficiency as the suffix tree without the need to store the input text string . Crochemore et al. proposed an \emph{offline} algorithm which transforms the suffix tree of into the LST of in…
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Taxonomy
TopicsAlgorithms and Data Compression · Network Packet Processing and Optimization · DNA and Biological Computing
