PPP-Codes for Large-Scale Similarity Searching
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00087959" target="_blank" >RIV/00216224:14330/16:00087959 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007/978-3-662-49214-7_2" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-662-49214-7_2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-662-49214-7_2" target="_blank" >10.1007/978-3-662-49214-7_2</a>
Alternative languages
Result language
angličtina
Original language name
PPP-Codes for Large-Scale Similarity Searching
Original language description
Many current applications need to organize data with respect to mutual similarity between data objects. A typical general strategy to retrieve objects similar to a given sample is to access and then refine a candidate set of objects. We propose an indexing and search technique that can significantly reduce the candidate set size by combination of several space partitionings. Specifically, we propose a mapping of objects from a generic metric space onto main memory codes using several pivot spaces; our search algorithm first ranks objects within each pivot space and then aggregates these rankings producing a candidate set reduced by two orders of magnitude while keeping the same answer quality. Our approach is designed to well exploit contemporary HW: (1) larger main memories allow us to use rich and fast index, (2) multi-core CPUs well suit our parallel search algorithm, and (3) SSD disks without mechanical seeks enable efficient selective retrieval of candidate objects.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXIV
ISBN
9783662492130
ISSN
0302-9743
e-ISSN
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Number of pages
27
Pages from-to
61-87
Publisher name
Springer
Place of publication
Berlin Heidelberg
Event location
Berlin Heidelberg
Event date
Jan 1, 2016
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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