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.
CITATION STYLE
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
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