Treffer: Improved Circular Dictionary Matching

Title:
Improved Circular Dictionary Matching
Contributors:
Bonizzoni, P, Makinen, V, Department of Computer Science, Algorithmic Bioinformatics
Publication Year:
2026
Collection:
Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto
Document Type:
Konferenz conference object
File Description:
application/pdf
Language:
English
ISBN:
978-3-95977-369-0
3-95977-369-2
Relation:
36th Annual Symposium On Combinatorial Pattern Matching, Cpm 2025; Leibniz International Proceedings In Informatics; Funded by the Helsinki Institute for Information Technology (HIIT).; Cotumaccio, N 2025, Improved Circular Dictionary Matching. in P Bonizzoni & V Makinen (eds), 36th Annual Symposium On Combinatorial Pattern Matching, Cpm 2025. Leibniz International Proceedings In Informatics, vol. 331, Schloss Dagstuhl Leibniz Center for Informatics, Symposium on Combinatorial Pattern Matching, Milan, Italy, 17/06/2025. https://doi.org/10.4230/LIPIcs.CPM.2025.18; conference; https://hdl.handle.net/10138/626667; 105008297145; 001570606300018
Rights:
cc_by ; info:eu-repo/semantics/openAccess ; openAccess
Accession Number:
edsbas.2FA90C9B
Database:
BASE

Weitere Informationen

The circular dictionary matching problem is an extension of the classical dictionary matching problem where every string in the dictionary is interpreted as a circular string: after reading the last character of a string, we can move back to its first character. The circular dictionary matching problem is motivated by applications in bioinformatics and computational geometry.In 2011, Hon et al. [ISAAC 2011] showed how to efficiently solve circular dictionary matching queries within compressed space by building on Mantaci et al.'s eBWT and Sadakane's compressed suffix tree. The proposed solution is based on the assumption that the strings in the dictionary are all distinct and non-periodic, no string is a circular rotation of some other string, and the strings in the dictionary have similar lengths.In this paper, we consider arbitrary dictionaries, and we show how to solve circular dictionary matching queries in O((m+ occ) log n) time within compressed space using n log sigma(1+ o(1))+ O(n)+ O( d log n) bits, where n is the total length of the dictionary, m is the length of the pattern, occ is the number of occurrences, d is the number of strings in the dictionary and sigma is the size of the alphabet. Our solution is based on an extension of the suffix array to arbitrary dictionaries and a sampling mechanism for the LCP array of a dictionary inspired by recent results in graph indexing and compression. ; Peer reviewed