Logo image
Diverse Near Neighbor Problem
Conference proceeding   Open access   Peer reviewed

Diverse Near Neighbor Problem

Sofiane Abbar, Sihem Amer-Yahia, Piotr Indyk, Sepideh Mahabadi and Kasturi Varadarajan
Proceedings of the 29th Annual Symposium on Computational Geometry (SoCG), pp.207-214
SoCG 2013 - Symposium on Computational Geometry
06/17/2013
DOI: 10.1145/2462356.2462401
url
https://doi.org/10.1145/2462356.2462401View
Published (Version of record) Open Access

Abstract

Motivated by the recent research on diversity-aware search, we investigate the k-diverse near neighbor reporting problem. The problem is defined as follows: given a query point q, report the maximum diversity set S of k points in the ball of radius r around q. The diversity of a set S is measured by the minimum distance between any pair of points in S (the higher, the better). We present two approximation algorithms for the case where the points live in a d-dimensional Hamming space. Our algorithms guarantee query times that are sub-linear in n and only polynomial in the diversity parameter k, as well as the dimension d. For low values of k, our algorithms achieve sub-linear query times even if the number of points within distance r from a query q is linear in n. To the best of our knowledge, these are the first known algorithms of this type that offer provable guarantees.
Computer Science Databases

Details

Metrics

10 Record Views
Logo image