Reverse Furthest Neighbors Query in Road Networks

Given a road network G = （V, E）, where V（E） denotes the set of vertices（edges） in G, a set of points of interest P and a query point q residing in G, the reverse furthest neighbors （RFNR） query in road networks fetches a set of points p ∈ P that take q as their furthest neighbor compared with all points in P ∪ {q}. This is the monochromatic RFNR （MRFNR） query. Another interesting version of RFNR query is the bichromatic reverse furthest neighbor （BRFNR） query. Given two sets of points P and Q, and a query point q ∈ Q, a BRFNR query fetches a set of points p ∈ P that take q as their furthest neighbor compared with all points in Q. This paper presents efficient algorithms for both MRFNR and BRFNR queries, which utilize landmarks and partitioning-based techniques. Experiments on real datasets confirm the efficiency and scalability of proposed algorithms.