Articolo in rivista, 2003, ENG, 10.1023/A:1025026030880
Dohnal V.; Gennaro C.; Savino P.; Zezula P.
Masaryk University, Brno, Czech Republic; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; Masaryk University, Brno, Czech Republic
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 grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.
Multimedia tools and applications 21 , pp. 9–33
metric spaces, similarity search, index structures, performance
Savino Pasquale, Gennaro Claudio
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 43688
Year: 2003
Type: Articolo in rivista
Creation: 2009-06-16 00:00:00.000
Last update: 2020-01-20 14:18:45.000
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:43688
DOI: 10.1023/A:1025026030880
ISI Web of Science (WOS): 000184619000002
Scopus: 2-s2.0-0042194447