http://www.cnr.it/ontology/cnr/individuo/prodotto/ID199514
Use of permutation prefixes for efficient and scalable approximate similarity search (Articolo in rivista)
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- 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)
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- [Online First 8 January 2011] (literal)
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- http://www.sciencedirect.com/science/article/pii/S0306457310001019 (literal)
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- 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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