Abstract
This paper proposes a spatial index structure based on a new space-partitioning method. Previous research proposed various high dimensional index structures. However, when dimensionality becomes high, the effectiveness of the spatial index structure disappears. This problem is called the “curse of dimensionality”. This paper focuses on the fact that the volume of high dimensional space is mostly occupied by its surface and then proposes a new surface index structure. The utility of this new surface spatial index structure is illustrated through a series of experiments.
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An, J., Chen, YP.P., Xu, Q. (2004). Surface Spatial Index Structure of High-Dimensional Space. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_40
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DOI: https://doi.org/10.1007/978-3-540-28651-6_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22881-3
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