Publication details

Separable Splits of Metric Data Sets

Authors

DOHNAL Vlastislav GENNARO Claudio SAVINO Pasquale ZEZULA Pavel

Year of publication 2001
Type Article in Proceedings
Conference SEBD01 - Italian Symposium on Database Systems
MU Faculty or unit

Faculty of Informatics

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:

You are running an old browser version. We recommend updating your browser to its latest version.

More info