Abstract
This chapter presents a new indexing scheme, the Subspace Coding Method (SCM), that offers high performance similarity retrieval. Indices in the R-tree family generate tree structure using MBRs (Minimum bounding rectangles) or MBSs (Minimum bounding spheres). Our proposed method is based on tree structure indices using MBRs (i.e. the R-tree, the R*-tree, the X-tree and so on), and newly introduced the notion of VBR (Virtual Bounding Rectangle). VBRs are rectangles which contain and approximate MBRs. Importantly, the notion of VBR is orthogonal to any other method in the field of spatial search and is introduced into any spatial indices using MBRs. Furthermore, we have introduced the Subspace Coding Method, which can compactly represent VBRs in tree structures, using its relative position within the parent VBR. The performance evaluation shows the superiority of our method for high-dimensional data.
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© 2000 Springer Science+Business Media New York
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Sakurai, Y., Yoshikawa, M., Uemura, S. (2000). Spatial Indexing by Virtual Bounding Rectangles for High-Dimensional Data. In: Tanaka, K., Ghandeharizadeh, S., Kambayashi, Y. (eds) Information Organization and Databases. The Springer International Series in Engineering and Computer Science, vol 579. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1379-7_19
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DOI: https://doi.org/10.1007/978-1-4615-1379-7_19
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