@article{journals/njc/Hyyro03,
	title = {A Bit-Vector Algorithm for Computing Levenshtein and Damerau Edit Distances.},
	author = {Heikki Hyyrö},
	journal = {Nord. J. Comput.},
	number = {1},
	pages = {29-39},
	url = {http://dblp.uni-trier.de/db/journals/njc/njc10.html#Hyyro03},
	volume = {10},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/27647daf53f3c46bff7ab25d918717763/thomas},
	description = {about Levenshtein and Damerau editdistanz from dblp},
	ee = {http://www.cs.helsinki.fi/njc/References/bollobas2001:409.html},
	keywords = {PDF damerau distance levenshtein matching uni }
}

@article{journals/njc/Hyyro03,
	title = {A Bit-Vector Algorithm for Computing Levenshtein and Damerau Edit Distances.},
	author = {Heikki Hyyrö},
	journal = {Nord. J. Comput.},
	number = {1},
	pages = {29-39},
	url = {http://dblp.uni-trier.de/db/journals/njc/njc10.html#Hyyro03},
	volume = {10},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/27647daf53f3c46bff7ab25d918717763/tmalsburg},
	description = {about Levenshtein and Damerau editdistanz from dblp},
	abstract = {The edit distance between strings A and B is defined as the minimum number of edit operations needed in converting A into B or vice versa. The Levenshtein edit distance allows three types of operations: an insertion, a deletion or a substitution of a character. The Damerau edit distance allows the previous three plus in addition a transposition between two adjacent characters. To our best knowledge the best current practical algorithms for computing these edit distances run in time O(dm) and O(⌈m/w⌉(n + σ)), where d is the edit distance between the two strings, m and n are their lengths (m ≤ n), w is the computer word size and σ is the size of the alphabet. In this paper we present an algorithm that runs in time O(⌈d/w⌉m + ⌈n/w⌉σ) or O(⌈d/w⌉n + ⌈m/w⌉σ). The structure of the algorithm is such, that in practice it is mostly suitable for testing whether the edit distance between two strings is within some pre-determined error threshold. We also present some initial test results with thresholded edit distance computation. In them our algorithm works faster than the original algorithm of Myers.
},
	ee = {http://www.cs.helsinki.fi/njc/References/bollobas2001:409.html},
	keywords = {B_scanpathsimilarity algorithm article editdistance stringsimilarity toread }
}

@article{journals/njc/Hyyro03,
	title = {A Bit-Vector Algorithm for Computing Levenshtein and Damerau Edit Distances.},
	author = {Heikki Hyyrö},
	journal = {Nord. J. Comput.},
	number = {1},
	pages = {29-39},
	url = {http://dblp.uni-trier.de/db/journals/njc/njc10.html#Hyyro03},
	volume = {10},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/27647daf53f3c46bff7ab25d918717763/dblp},
	description = {dblp},
	date = {2004-01-14},
	keywords = {dblp }
}