Average complexity of backward q-gram string matching algorithms

Many efficient string matching algorithms make use of q-grams and process the text in windows which are read backward. In this paper we provide a framework for analyzing the average case complexity of these algorithms taking into account the statistical dependencies between overlapping q-grams. We a...

Full description

Saved in:
Bibliographic Details
Published in:Information processing letters Vol. 112; no. 11; pp. 433 - 437
Main Author: Salmela, Leena
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 15.06.2012
Elsevier Sequoia S.A
Subjects:
Algorithms
Analysis of algorithms
Average case complexity
Complexity
Computer science
Data processing
Mathematical problems
Optimization
String matching
Studies
Texts
Average case complexity
Analysis of algorithms
String matching
ISSN:0020-0190, 1872-6119
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Many efficient string matching algorithms make use of q-grams and process the text in windows which are read backward. In this paper we provide a framework for analyzing the average case complexity of these algorithms taking into account the statistical dependencies between overlapping q-grams. We apply this to the q-gram Boyer–Moore–Horspool algorithm adapted to various string matching problems and show that the algorithm is optimal on average. ► We study the average case complexity of string matching algorithms that use q-grams. ► We take into account the statistical dependencies of overlapping q-grams. ► We show that q-gram Boyer–Moore–Horspool style algorithms are average optimal.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0020-0190
1872-6119
DOI:10.1016/j.ipl.2012.02.010