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Searching in metric spaces (2001)
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@MISC{Chávez01searchingin,
author = {Edgar Chávez and Gonzalo Navarro and Ricardo Baeza-yates and José Luis Marroquín},
title = {Searching in metric spaces},
year = {2001}
}
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Abstract
The problem of searching the elements of a set that are close to a given query element under some similarity criterion has a vast number of applications in many branches of computer science, from pattern recognition to textual and multimedia information retrieval. We are interested in the rather general case where the similarity criterion defines a metric space, instead of the more restricted case of a vector space. Many solutions have been proposed in different areas, in many cases without cross-knowledge. Because of this, the same ideas have been reconceived several times, and very different presentations have been given for the same approaches. We present some basic results that explain the intrinsic difficulty of the search problem. This includes a quantitative definition of the elusive concept of “intrinsic dimensionality. ” We also present a unified
Keyphrases
similarity criterion different area intrinsic dimensionality multimedia information retrieval subject descriptor different presentation nonnumerical algorithm quantitative definition many case vector space basic result content analysis general case query element geometrical problem computer science metric space physical design access method intrinsic difficulty problem computation vast number many solution unified category information storage search problem restricted case several time pattern recognition elusive concept discrete structure problem complexity database management many branch
