King's College London

Research portal

On-Line Pattern Matching on Similar Texts

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

Roberto Grossi, Costas S. Iliopoulos, Chang Liu, Nadia Pisanti, Solon P. Pissis, Ahmad Retha, Giovanna Rosone, Fatima Vayani, Luca Versari

Original languageEnglish
Title of host publication28th Annual Symposium on Combinatorial Pattern Matching (CPM 2017)
EditorsJakub Radoszewski Juha Kärkkäinen, Wojciech Rytter
Place of PublicationDagstuhl, Germany
PublisherSchloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Pages9:1-9:14
Number of pages14
Volume78
ISBN (Print)978-3-95977-039-2
DOIs
Publication statusPublished - 2017

Publication series

NameLeibniz International Proceedings in Informatics (LIPIcs)
PublisherSchloss Dagstuhl--Leibniz-Zentrum fuer Informatik

Documents

King's Authors

Abstract

Pattern matching on a set of similar texts has received much attention, especially recently, mainly due to its application in cataloguing human genetic variation. In particular, many different algorithms have been proposed for the off-line version of this problem; that is, constructing a compressed index for a set of similar texts in order to answer pattern matching queries efficiently. However, the on-line, more fundamental, version of this problem is a rather undeveloped topic. Solutions to the on-line version can be beneficial for a number of reasons; for instance, efficient on-line solutions can be used in combination with partial indexes as practical trade-offs. We make here an attempt to close this gap via proposing two efficient algorithms for this problem. Notably, one of the algorithms requires time linear in the size of the texts’ representation, for short patterns. Furthermore, experimental results confirm our theoretical findings in practical terms.

Download statistics

No data available

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454