Reverse Furthest Neighbors in Spatial Databases. Bin Yao , Feifei Li, Piyush Kumar Florida State University . A Novel Query Type. Reverse Furthest Neighbors (RFN) Given a point q and a data set P, find the set of points in P that take q as their furthest neighbor Two versions :
Reverse Furthest Neighbors in Spatial Databases
Bin Yao, Feifei Li, Piyush Kumar
Florida State University
Given a point q and a data set P, find the set of points in P that take q as their furthest neighbor
P: a set of customers
Q: a set of business competitors offering similar products
A distance measure reflecting the rating of customer(p) to competitor(q)’s product.
A larger distance indicates a lower preference.
For any competitor in Q, an interesting query is to discover the customers that dislike his product the most among all competing products in the market.
Lemma: Any point from the furthest Voronoi cell(fvc) of p takes p as its furthest neighbor among all points in P.
Lemma: the furthest point for p from Q is always a vertex of
the convex hull of Q. In a reverse angle, only vertices of CH have RFN.
// compute only once
The qhull algorithm
Adapt qhull to R-tree
Limitation: query group size may not fit in memory
Solution: Approximate convex hull of Q (Dudley’s approximation: the core set idea)
Number of IOs
CPU: vary A, Q=1000
IOs: vary A, Q=1000
BRFN number of IOs
MRFN number of IOs
IOs: vary Q,A=3%
CPU: vary |Q|,A=3%