Publication details
Organizing Similarity Spaces using Metric Hulls
| Authors | |
|---|---|
| Year of publication | 2021 |
| Type | Article in Proceedings |
| Conference | 14th International Conference on Similarity Search and Applications (SISAP 2021) |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/978-3-030-89657-7_1 |
| Keywords | metric-hull tree; metric hull; index structure; nearest-neighbors query; similarity search |
| Attached files | |
| Description | 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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