Organizing Similarity Spaces using Metric Hulls
| Autoři | |
|---|---|
| Rok publikování | 2021 |
| Druh | Článek ve sborníku |
| Konference | 14th International Conference on Similarity Search and Applications (SISAP 2021) |
| Fakulta / Pracoviště MU | |
| Citace | |
| Doi | http://dx.doi.org/10.1007/978-3-030-89657-7_1 |
| Klíčová slova | metric-hull tree; metric hull; index structure; nearest-neighbors query; similarity search |
| Přiložené soubory | |
| Popis | A novel concept of a metric hull has recently been introduced to encompass a set of objects by a few selected border objects. Following one of the metric-hull computation methods that generate a hierarchy of metric hulls, we introduce a metric index structure for unstructured and complex data, a Metric Hull Tree (MH-tree). We propose a construction of MH-tree by a bulk-loading procedure and outline an insert operation. With respect to the design of the tree, we provide an implementation of an approximate $k$NN search operation. Finally, we utilized the Profimedia dataset to evaluate various building and ranking strategies of MH-tree and compared the results with M-tree. |
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