TY - GEN
T1 - Weighted ancestors in suffix trees
AU - Gawrychowski, Paweł
AU - Lewenstein, Moshe
AU - Nicholson, Patrick K.
PY - 2014
Y1 - 2014
N2 - The classical, ubiquitous, predecessor problem is to construct a data structure for a set of integers that supports fast predecessor queries. Its generalisation to weighted trees, a.k.a. the weighted ancestor problem, has been extensively explored and successfully reduced to the predecessor problem. It is known that any data structure solution for the weighted ancestor problem that occupies O(n polylog(n)) space must have Ω(loglogn) query time, if the weights are drawn from a polynomially bounded universe. Perhaps the most important and frequent application of the weighted ancestors problem is for suffix trees. It has been a long-standing open question whether the weighted ancestors problem has better bounds for suffix trees. We answer this question positively: we show that a suffix tree built for a text w[1.n] can be preprocessed using O(n) extra space, so that queries can be answered in O(1) time. Thus we improve the running times of several applications. Our improvement is based on a number of data structure tools and a periodicity-based insight into the combinatorial structure of a suffix tree.
AB - The classical, ubiquitous, predecessor problem is to construct a data structure for a set of integers that supports fast predecessor queries. Its generalisation to weighted trees, a.k.a. the weighted ancestor problem, has been extensively explored and successfully reduced to the predecessor problem. It is known that any data structure solution for the weighted ancestor problem that occupies O(n polylog(n)) space must have Ω(loglogn) query time, if the weights are drawn from a polynomially bounded universe. Perhaps the most important and frequent application of the weighted ancestors problem is for suffix trees. It has been a long-standing open question whether the weighted ancestors problem has better bounds for suffix trees. We answer this question positively: we show that a suffix tree built for a text w[1.n] can be preprocessed using O(n) extra space, so that queries can be answered in O(1) time. Thus we improve the running times of several applications. Our improvement is based on a number of data structure tools and a periodicity-based insight into the combinatorial structure of a suffix tree.
UR - http://www.scopus.com/inward/record.url?scp=84958532053&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-662-44777-2_38
DO - https://doi.org/10.1007/978-3-662-44777-2_38
M3 - منشور من مؤتمر
SN - 9783662447765
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 455
EP - 466
BT - Algorithms, ESA 2014 - 22nd Annual European Symposium, Proceedings
PB - Springer Verlag
T2 - 22nd Annual European Symposium on Algorithms, ESA 2014
Y2 - 8 September 2014 through 10 September 2014
ER -