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Cahsai et al., 2017 - Google Patents

Scaling k-nearest neighbours queries (the right way)

Cahsai et al., 2017

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Document ID
13362116103641496990
Author
Cahsai A
Ntarmos N
Anagnostopoulos C
Triantafillou P
Publication year
Publication venue
2017 IEEE 37th international conference on distributed computing systems (ICDCS)

External Links

Snippet

Recently parallel/distributed processing approaches have been proposed for processing k- Nearest Neighbours (kNN) queries over very large (multidimensional) datasets aiming to ensure scalability. However, this is typically achieved at the expense of efficiency. With this …
Continue reading at eprints.gla.ac.uk (PDF) (other versions)

Classifications

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    • G06F17/30477—Query execution
    • G06F17/30483—Query execution of query operations
    • G06F17/30486—Unary operations; data partitioning operations
    • G06F17/30489—Aggregation and duplicate elimination
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