Reverse Query-Aware Locality-Sensitive Hashing for High-Dimensional Furthest Neighbor Search

The c-Approximate Furthest Neighbor (c-AFN) search is a fundamental problem in many applications. However, existing hashing schemes are designed for internal memory. The old techniques for external memory, such as furthest point Voronoi diagram and the tree-based methods, are only suitable for the low-dimensional case. In this paper, we introduce a novel concept of Reverse Locality-Sensitive Hashing (RLSH) family which is directly designed for c-AFN search. Accordingly, we propose two novel hashing schemes RQALSH and RQALSH for highdimensional c-AFN search over external memory. Experimental results validate the efficiency and effectiveness of RQALSH and RQALSH.