Similarity Search with Implicit Object Features

Driven by many real applications, in this paper we study the problem of similarity search with implicit object features; that is, the features of each object are not pre-computed/evaluated. As the existing similarity search techniques are not applicable, a novel and efficient algorithm is developed...

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Bibliographic Details
Published inAdvances in Web-Age Information Management pp. 150 - 161
Main Authors Luo, Yi, Liu, Zheng, Lin, Xuemin, Wang, Wei, Yu, Jeffrey Xu
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
SeriesLecture Notes in Computer Science
Online AccessGet full text
ISBN9783540292272
3540292276
ISSN0302-9743
1611-3349
DOI10.1007/11563952_14

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Summary:Driven by many real applications, in this paper we study the problem of similarity search with implicit object features; that is, the features of each object are not pre-computed/evaluated. As the existing similarity search techniques are not applicable, a novel and efficient algorithm is developed in this paper to approach the problem. The R-tree based algorithm consists of two steps: feature evaluation and similarity search. Our performance evaluation demonstrates that the algorithm is very efficient for large spatial datasets.
ISBN:9783540292272
3540292276
ISSN:0302-9743
1611-3349
DOI:10.1007/11563952_14