Approximate Furthest Neighbor in High Dimensions

  title={Approximate Furthest Neighbor in High Dimensions},
  author={Rasmus Pagh and Francesco Silvestri and Johan Sivertsen and Matthew Skala},
Much recent work has been devoted to approximate nearest neighbor queries. Motivated by applications in recommender systems, we consider approximate furthest neighbor (AFN) queries. We present a simple, fast, and highly practical data structure for answering AFN queries in high-dimensional Euclidean space. We build on the technique of Indyk (SODA 2003), storing random projections to provide sublinear query time for AFN. However, we introduce a different query algorithm, improving on Indyk’s… CONTINUE READING

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