PP-Index: using permutation prefixes for efficient and scalable similarity search (Extended Abstract) (Contributo in atti di convegno)

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  • PP-Index: using permutation prefixes for efficient and scalable similarity search (Extended Abstract) (Contributo in atti di convegno) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
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  • Esuli A. (2010)
    PP-Index: using permutation prefixes for efficient and scalable similarity search (Extended Abstract)
    in 18th Italian Symposium on Advanced Database Systems, Rimini, Italy
    (literal)
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  • Esuli A. (literal)
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  • In: SEBD 2010 - 18th Italian Symposium on Advanced Database Systems (Rimini, Italy, 20-23 June 2010). Atti, pp. 318 - 325. Sonia Bergamaschi, Stefano Lodi, Riccardo Martoglia, Claudio Sartori (eds.). Editrice Esculapio, 2010. (literal)
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  • ABSTRACT: The Permutation Prefix Index (PP-Index) is a data structure that allows to perform efficient approximate similarity search. It is a permutation-based index, which is 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 biased toward efficiency. We show how the effectiveness can 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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  • PP-Index: using permutation prefixes for efficient and scalable similarity search (Extended Abstract) (literal)
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