SS+ tree: an improved index structure for similarity searches in a high-dimensional feature space

Ruth Kurniawati; Jesse S. Jin; John A. Shepard

doi:10.1117/12.263400

15 January 1997 SS⁺ tree: an improved index structure for similarity searches in a high-dimensional feature space

Ruth Kurniawati, Jesse S. Jin, John A. Shepard

Proceedings Volume 3022, Storage and Retrieval for Image and Video Databases V; (1997) https://doi.org/10.1117/12.263400
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

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.

Citation Download Citation

Ruth Kurniawati, Jesse S. Jin, and John A. Shepard "SS⁺ tree: an improved index structure for similarity searches in a high-dimensional feature space", Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); https://doi.org/10.1117/12.263400

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