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DBM-Tree: Trading height-balancing for performance in metric access methods

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Figure

Figure 1. Exemplifying a node split using the 2-Clusters() algorithm: (a) before the split, (b) forming C groups withunique nodes, (c) 2 final groups, and (d) the final nodes created with the chosen representatives.
Table 2. Maximum height of the tree for each dataset tested.Cities4
Figure 2. Visualization of the DBM-MM structure for the Cities dataset. (a) with the covering radius of the nodes; and(b) only the objects
Figure 4. Comparison of the average number of distance calculations (first column), average number of disk accesses(second column) and total processing time in seconds (third column) of DBM-tree, Slim-tree and M-tree, for Rq andkNNq queries for the ColorHisto ((a), (b) and (c) - Rq), MedHisto ((d), (e) and (f) - kNNq), Synt16D ((g), (h) and (i)- Rq) and Synt256D ((j), (k) and (l) - kNNq) datasets.
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