PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Esuli A. Use of permutation prefixes for efficient and scalable approximate similarity search. In: Information Processing & Management, vol. 48 (5) pp. 889 - 902. Elsevier, 2012.
 
 
Abstract
(English)
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.
URL: http://www.sciencedirect.com/science/article/pii/S0306457310001019
DOI: http://dx.doi.org/10.1016/j.ipm.2010.11.011
Subject Approximate similarity search
Metric space
Scalability
H.3.3 Information Search and Retrieval - search process
E.1 Data structures


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