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Scaling KNN Computation over Large Graphs on a PC
Abstract : This paper proposes a novel approach to compute K-Nearest Neighbors (KNN) algorithm on a large set of users by lever-aging disk and memory efficiently on a commodity PC. The system is designed to minimize random accesses to disk as well as the amount of data loaded/unloaded from/to disk so as to better utilize the computational power, thus improving the algorithmic efficiency.
Keywords :
K-nearest neighbors
Dynamic Graphs
Cited literature [3 references]
https://hal.inria.fr/hal-01095557
Contributor : Javier Olivares Connect in order to contact the contributor
Submitted on : Thursday, December 18, 2014 - 1:48:40 PM
Last modification on : Thursday, January 20, 2022 - 4:20:00 PM
Long-term archiving on: : Monday, March 23, 2015 - 1:20:38 PM
Contributor : Javier Olivares Connect in order to contact the contributor
Submitted on : Thursday, December 18, 2014 - 1:48:40 PM
Last modification on : Thursday, January 20, 2022 - 4:20:00 PM
Long-term archiving on: : Monday, March 23, 2015 - 1:20:38 PM
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Chiluka-Kermarrec-Olivares.pdf
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