Similarity search with implicit object features

1Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Luo, Y., Liu, Z., Lin, X., Wang, W., & Yu, J. X. (2005). Similarity search with implicit object features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3739 LNCS, pp. 150–161). https://doi.org/10.1007/11563952_14

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free