Title
Efficient Algorithms for Computing the Inner Edit Distance of a Regular Language via Transducers.
Abstract
The concept of edit distance and its variants has applications in many areas such as computational linguistics, bioinformatics, and synchronization error detection in data communications. Here, we revisit the problem of computing the inner edit distance of a regular language given via a Nondeterministic Finite Automaton (NFA). This problem relates to the inherent maximal error-detecting capability of the language in question. We present two efficient algorithms for solving this problem, both of which execute in time O(r(2)n(2)d), where r is the cardinality of the alphabet involved, n is the number of transitions in the given NFA, and d is the computed edit distance. We have implemented one of the two algorithms and present here a set of performance tests. The correctness of the algorithms is based on the connection between word distances and error detection and the fact that nondeterministic transducers can be used to represent the errors (resp., edit operations) involved in error-detection (resp., in word distances).
Year
DOI
Venue
2018
10.3390/a11110165
ALGORITHMS
Keywords
Field
DocType
algorithms,automata,complexity,edit distance,implementation,transducers,regular language
Edit distance,Nondeterministic finite automaton,Nondeterministic algorithm,Correctness,Automaton,Computational linguistics,Cardinality,Algorithm,Regular language,Mathematics
Journal
Volume
Issue
ISSN
11
11
1999-4893
Citations 
PageRank 
References 
0
0.34
7
Authors
4
Name
Order
Citations
PageRank
Lila Kari11123124.45
Stavros Konstantinidis228331.10
Steffen Kopecki3689.97
Meng Yang4102855.17