Separable Splits of Metric Data Sets
| Authors | |
|---|---|
| Year of publication | 2001 |
| Type | Article in Proceedings |
| Conference | SEBD01 - Italian Symposium on Database Systems |
| MU Faculty or unit | |
| Citation | |
| Field | Informatics |
| Keywords | data partitioning; data exclusion; metric space |
| Description | In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types (such as image, video, or audio features) grows, the traditional partitioning techniques based on total ordering of data can not typically be applied. We consider the problem of partitioning data collections from generic metric spaces, where total ordering of objects does not exists, and where only distances between pairs of objects can be determined. We study the elementary type of partitioning that splits a given collection into two well-separated subsets, allowing some objects to be excluded from the partitioning process. Five implementation techniques of separable splits are proposed and proved for correctness. |
| Related projects: |