TY - GEN
T1 - Online algorithms for constructing linear-size suffix trie
AU - Hendrian, Diptarama
AU - Takagi, Takuya
AU - Inenaga, Shunsuke
N1 - Funding Information:
Funding Diptarama Hendrian: Supported by JSPS KAKENHI Grant Number JP19K20208. Shunsuke Inenaga: Supported by JSPS KAKENHI Grant Number JP17H01697.
Publisher Copyright:
© Diptarama Hendrian, Takuya Takagi, and Shunsuke Inenaga.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a string T of length n has O(n) nodes and edges, and the string label of each edge is encoded by a pair of positions in T. Thus, even after the tree is built, the input text T needs to be kept stored and random access to T is still needed. The linear-size suffix tries (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 a string T of length n occupies O(n) total space, and supports pattern matching and other tasks in the same efficiency as the suffix tree without the need to store the input text T. Crochemore et al. proposed an offline algorithm which transforms the suffix tree of T into the LST of T in O(nlog σ) time and O(n) space, where σ is the alphabet size. In this paper, we present two types of online algorithms which “directly” construct the LST, from right to left, and from left to right, without constructing the suffix tree as an intermediate structure. Both algorithms construct the LST incrementally when a new symbol is read, and do not access to the previously read symbols. The right-to-left construction algorithm works in O(nlog σ) time and O(n) space and the left-to-right construction algorithm works in O(n(log σ + log n/log log n)) time and O(n) space. The main feature of our algorithms is that the input text does not need to be stored.
AB - The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a string T of length n has O(n) nodes and edges, and the string label of each edge is encoded by a pair of positions in T. Thus, even after the tree is built, the input text T needs to be kept stored and random access to T is still needed. The linear-size suffix tries (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 a string T of length n occupies O(n) total space, and supports pattern matching and other tasks in the same efficiency as the suffix tree without the need to store the input text T. Crochemore et al. proposed an offline algorithm which transforms the suffix tree of T into the LST of T in O(nlog σ) time and O(n) space, where σ is the alphabet size. In this paper, we present two types of online algorithms which “directly” construct the LST, from right to left, and from left to right, without constructing the suffix tree as an intermediate structure. Both algorithms construct the LST incrementally when a new symbol is read, and do not access to the previously read symbols. The right-to-left construction algorithm works in O(nlog σ) time and O(n) space and the left-to-right construction algorithm works in O(n(log σ + log n/log log n)) time and O(n) space. The main feature of our algorithms is that the input text does not need to be stored.
UR - http://www.scopus.com/inward/record.url?scp=85068052163&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85068052163&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.CPM.2019.30
DO - 10.4230/LIPIcs.CPM.2019.30
M3 - Conference contribution
AN - SCOPUS:85068052163
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 30th Annual Symposium on Combinatorial Pattern Matching, CPM 2019
A2 - Pisanti, Nadia
A2 - Pissis, Solon P.
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 30th Annual Symposium on Combinatorial Pattern Matching, CPM 2019
Y2 - 18 June 2019 through 20 June 2019
ER -