The Extended Edit Distance Metric
Information Retrieval
2010-06-18 v1
Abstract
Similarity search is an important problem in information retrieval. This similarity is based on a distance. Symbolic representation of time series has attracted many researchers recently, since it reduces the dimensionality of these high dimensional data objects. We propose a new distance metric that is applied to symbolic data objects and we test it on time series data bases in a classification task. We compare it to other distances that are well known in the literature for symbolic data objects. We also prove, mathematically, that our distance is metric.
Cite
@article{arxiv.0709.4669,
title = {The Extended Edit Distance Metric},
author = {Muhammad Marwan Muhammad Fuad and Pierre-François Marteau},
journal= {arXiv preprint arXiv:0709.4669},
year = {2010}
}
Comments
Technical report