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Conference Papers Year : 2016

Fast distributed k-nn graph update

Fabio Pulvirenti
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Pietro Michiardi
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Wim Mees
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In this paper, we present an approximate algorithm that is able to quickly modify a large distributed k-nn graph by adding or removing nodes. The algorithm produces an approximate graph that is highly similar to the graph computed using a naïve approach, although it requires the computation of far fewer similarities. To achieve this goal, it relies on a novel, distributed graph based search procedure. All these algorithms are also experimentally evaluated, using both euclidean and non-euclidean datasets.
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hal-01525697 , version 1 (29-05-2017)



Thibault Debatty, Fabio Pulvirenti, Pietro Michiardi, Wim Mees. Fast distributed k-nn graph update. 2016 IEEE International Conference on Big Data, Dec 2016, Washington, DC, United States. pp.3308-3317, ⟨10.1109/BigData.2016.7840990⟩. ⟨hal-01525697⟩


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