Use of permutation prefixes for efficient and scalable approximate similarity search (Articolo in rivista)

Type
Label
  • Use of permutation prefixes for efficient and scalable approximate similarity search (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.ipm.2010.11.011 (literal)
Alternative label
  • Esuli A. (2012)
    Use of permutation prefixes for efficient and scalable approximate similarity search
    in Information processing & management
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Esuli A. (literal)
Pagina inizio
  • 889 (literal)
Pagina fine
  • 902 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • [Online First 8 January 2011] (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.sciencedirect.com/science/article/pii/S0306457310001019 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 48 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 5 (literal)
Note
  • PuMa (literal)
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy; (literal)
Titolo
  • Use of permutation prefixes for efficient and scalable approximate similarity search (literal)
Abstract
  • We present the Permutation Prefix Index (this work is a revised and extended version of Esuli (2009b), presented at the 2009 LSDS-IR Workshop, held in Boston) (PP-Index), an index data structure that supports efficient approximate similarity search. The PP-Index belongs to the family of the permutation-based indexes, which are based on representing any indexed object with \"its view of the surrounding world\", i.e., a list of the elements of a set of reference objects sorted by their distance order with respect to the indexed object. In its basic formulation, the PP-Index is strongly biased toward efficiency. We show how the effectiveness can easily reach optimal levels just by adopting two \"boosting\" strategies: multiple index search and multiple query search, which both have nice parallelization properties. We study both the efficiency and the effectiveness properties of the PP-Index, experimenting with collections of sizes up to one hundred million objects, represented in a very high-dimensional similarity space. (literal)
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