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Jun 9, 2017 · Near neighbor search (NNS) has been traditionally addressed from an algorithmic perspective, that is, given a dataset and a distance ...
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In this paper we propose a novel approach to solving the nearest neighbor search problem. We propose to build a data structure where the greedy search algorithm ...
Locality sensitive hashing (LSH) is a widely popular technique used in approximate nearest neighbor (ANN) search.
Approximate nearest neighbor search (ANNS) is a funda- mental problem in databases and data mining. A scalable ANNS algorithm should be both memory-efficient ...
In this paper we introduce three searching algorithms generalizing to local search other than greedy, and experimentally prove that our approach improves ...
Apr 22, 2011 · The most popular is Locality-Sensitive Hashing (LSH), which maps a set of points in a high-dimensional space into a set of bins, ie, a hash table.
Sep 23, 2016 · In this paper, we propose EFANNA, an extremely fast approximate nearest neighbor search algorithm based on kNN Graph. Efanna nicely combines the ...
By only searching the nodes near the query node, local methods have the potential to support more efficient query. However, most existing local search methods ...
We propose two solutions for both nearest neigh- bors and range search problems. For the nearest neighbors problem, we propose a c-approximate ...
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) ...