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.
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Luo, Y., Liu, Z., Lin, X., Wang, W., Yu, J.X. (2005). Similarity Search with Implicit Object Features. In: Fan, W., Wu, Z., Yang, J. (eds) Advances in Web-Age Information Management. WAIM 2005. Lecture Notes in Computer Science, vol 3739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11563952_14
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DOI: https://doi.org/10.1007/11563952_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29227-2
Online ISBN: 978-3-540-32087-6
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