http://www.cnr.it/ontology/cnr/individuo/prodotto/ID91487
Separable Splits of Metric Data Sets (Contributo in atti di convegno)
- Type
- Label
- Separable Splits of Metric Data Sets (Contributo in atti di convegno) (literal)
- Anno
- 2001-01-01T00:00:00+01:00 (literal)
- Alternative label
Dohnal V.; Gennaro C.; Savino P.; Zezula P. (2001)
Separable Splits of Metric Data Sets
in Sistemi Evoluti per Basi di Dati. Atti del IX Congresso Nazionale SEBD 2001, Venezia, Italy, 27/04/2001
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Dohnal V.; Gennaro C.; Savino P.; Zezula P. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- Sistemi Evoluti per Basi di Dati. Atti del IX Congresso Nazionale SEBD 2001 (Venezia, Italy, 27-29 June 2001), 45-62. Augusto Celentano, Letizia Tanca e paolo Tiberio (cur.). (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- CNR-ISTI, Pisa, Masaryk University, Brno, Czech Republic (literal)
- Titolo
- Separable Splits of Metric Data Sets (literal)
- Abstract
- 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. The rst two are simple extensions of the known ball partitioning and the generalized
hyperplane approaches, the third is an advanced hyperplane partitioning. The additional two techniques
are completely original and are based on the elliptic and pseudo-elliptic geometric strategies. Effectiveness
of all techniques is evaluated in terms of their ability to equalize the separable set sizes, and to minimize
the number of excluded objects. Proposed techniques are evaluated on three large data les. (literal)
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