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.
https://hal.inria.fr/hal-01095557
Contributeur : Javier Olivares
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Soumis le : jeudi 18 décembre 2014 - 13:48:40
Dernière modification le : mercredi 16 mai 2018 - 11:23:13
Document(s) archivé(s) le : lundi 23 mars 2015 - 13:20:38
Nitin Chiluka, Anne-Marie Kermarrec, Javier Olivares. Scaling KNN Computation over Large Graphs on a PC. Middleware 2014, Dec 2014, Bourdeaux, France. 〈10.1145/2678508.2678513〉. 〈hal-01095557〉
