Searching dynamic point sets in spaces with bounded doubling dimension

Richard Cole, Lee Ad Gottlieb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a new data structure that facilitates approximate nearest neighbor searches on a dynamic set of points in a metric space that has a bounded doubling dimension. Our data structure has linear size and supports insertions and deletions in O(log n) time, and finds a (1 + ε)-approximate nearest neighbor in time O(log n) + (1/ε)O(1). The search and update times hide multiplicative factors that depend on the doubling dimension; the space does not. These performance times are independent of the aspect ratio (or spread) of the points.

Original languageEnglish (US)
Title of host publicationSTOC'06
Subtitle of host publicationProceedings of the 38th Annual ACM Symposium on Theory of Computing
PublisherAssociation for Computing Machinery
Pages574-583
Number of pages10
ISBN (Print)1595931341, 9781595931344
DOIs
StatePublished - 2006
Event38th Annual ACM Symposium on Theory of Computing, STOC'06 - Seattle, WA, United States
Duration: May 21 2006May 23 2006

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
Volume2006
ISSN (Print)0737-8017

Other

Other38th Annual ACM Symposium on Theory of Computing, STOC'06
CountryUnited States
CitySeattle, WA
Period5/21/065/23/06

Keywords

  • Approximate nearest neighbor search

ASJC Scopus subject areas

  • Software

Fingerprint Dive into the research topics of 'Searching dynamic point sets in spaces with bounded doubling dimension'. Together they form a unique fingerprint.

Cite this