BIGDATA 2016, 2016 IEEE International Conference on Big Data, December 5-8, 2016, Washington, USA
In this paper, we present an approximate algorithm that is able to quickly modify a large distributed fc-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.
Type:
Conférence
City:
Washington
Date:
2016-12-05
Department:
Data Science
Eurecom Ref:
5133
Copyright:
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