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Proceedings Paper

SS+ tree: an improved index structure for similarity searches in a high-dimensional feature space
Author(s): Ruth Kurniawati; Jesse S. Jin; John A. Shepard
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Paper Abstract

In this paper, we describe the SS+-tree, a tree structure for supporting similarity searches in a high- dimensional Euclidean space. Compared to the SS-tree, the tree uses a tighter bounding sphere for each node which is an approximation to the smallest enclosing sphere and it also makes a better use of the clustering property of the available data by using a variant of the k-means clustering algorithm as the split heuristic for its nodes. A local reorganization rule is also introduced during the tree building to reduce the overlapping between the nodes' bounding spheres.

Paper Details

Date Published: 15 January 1997
PDF: 11 pages
Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); doi: 10.1117/12.263400
Show Author Affiliations
Ruth Kurniawati, Univ. of New South Wales (Australia)
Jesse S. Jin, Univ. of New South Wales (Australia)
John A. Shepard, Univ. of New South Wales (Australia)


Published in SPIE Proceedings Vol. 3022:
Storage and Retrieval for Image and Video Databases V
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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