Semi-local string comparison: algorithmic techniques and applications
Alexander Tiskin

TL;DR
This paper introduces the semi-local LCS problem, a comprehensive string comparison method that enhances traditional techniques by providing detailed similarity measures, with broad applications in biology, geometry, and algorithms.
Contribution
It formalizes the semi-local LCS problem, develops efficient algorithms for it, and demonstrates its versatility across various fields and problem types.
Findings
Provides a new framework for detailed string similarity analysis
Develops efficient algorithms for semi-local LCS computation
Shows applications in biology, geometry, and permutation problems
Abstract
A classical measure of string comparison is given by the longest common subsequence (LCS) problem on a pair of strings. We consider its generalisation, called the semi-local LCS problem, which arises naturally in many string-related problems. The semi-local LCS problem asks for the LCS scores for each of the input strings against every substring of the other input string, and for every prefix of each input string against every suffix of the other input string. Such a comparison pattern provides a much more detailed picture of string similarity than a single LCS score; it also arises naturally in many string-related problems. In fact, the semi-local LCS problem turns out to be fundamental for string comparison, providing a powerful and flexible alternative to classical dynamic programming. It is especially useful when the input to a string comparison problem may not be available all at…
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Taxonomy
TopicsAlgorithms and Data Compression · Natural Language Processing Techniques · Network Packet Processing and Optimization
