A novel improvement to the R*-tree spatial index using gain/loss metrics
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Improving the R*-tree with outlier handling techniques
Proceedings of the 13th annual ACM international workshop on Geographic information systems
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Non-uniformity in data extents is a general characteristic of spatial data. Indexing such non-uniform data using conventional spatial index structures such as R/sup */-trees is inefficient for two reasons: (1) the non-uniformity increases the likelihood of overlapping index entries, and (2) clustering of non-uniform data is likely to index more dead space than clustering of uniform data. To reduce the impact of these anomalies, we propose a new scheme that promotes data objects to higher levels in tree-based index structures. We examine two criteria for promotion of data objects and evaluate their relative merits using an R*-tree. In experiments on cartographic data, we observe that our promotion criteria yield up to 45% improvement in query performance for an R*-tree.