DocumentCode :
3334550
Title :
A contextual normalised edit distance
Author :
de la Higuer, Colin ; Micó, Luisa
Author_Institution :
Lab. Hubert Curien, Univ. de St.-Etienne, St. Etienne
fYear :
2008
fDate :
7-12 April 2008
Firstpage :
354
Lastpage :
361
Abstract :
In order to better fit a variety of pattern recognition problems over strings, using a normalised version of the edit or Levenshtein distance is considered to be an appropriate approach. The goal of normalisation is to take into account the lengths of the strings. We define a new normalisation, contextual, where each edit operation is divided by the length of the string on which the edit operation takes place. We prove that this contextual edit distance is a metric and that it can be computed through an extension of the usual dynamic programming algorithm for the edit distance. We also provide a fast heuristic which nearly always returns the same result and we show over several experiments that the distance obtains good results in classification tasks and has a low intrinsic dimension in comparison with other normalised edit distances.
Keywords :
dynamic programming; pattern classification; string matching; Levenshtein distance; classification task; contextual normalised edit distance; dynamic programming algorithm; pattern recognition problem; Acceleration; Computational biology; Dynamic programming; Heuristic algorithms; Mathematics; Measurement standards; Pattern recognition; Space exploration; Topology; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering Workshop, 2008. ICDEW 2008. IEEE 24th International Conference on
Conference_Location :
Cancun
Print_ISBN :
978-1-4244-2161-9
Electronic_ISBN :
978-1-4244-2162-6
Type :
conf
DOI :
10.1109/ICDEW.2008.4498345
Filename :
4498345
Link To Document :
بازگشت