Index Maintenance Strategy and Cost Model for Extended Cluster Pruning

Anders Munck Højsgaard, Björn Thór Jónsson, Philippe Bonnet

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

With today’s dynamic multimedia collections, maintenance of high-dimensional indexes is an important, yet understudied topic. Extended Cluster Pruning (eCP) is a highly-scalable approximate indexing approach based on clustering, that is targeted at stable performance in a disk-based scenario. In this work, we propose an index maintenance strategy for the eCP index, which utilizes the tree structure of the index and its approximate nature. We then develop a cost model for the strategy and evaluate its cost using a simulation model.
OriginalsprogEngelsk
TitelProceedings of the International Conference on Similarity Search and Applications (SISAP)
Antal sider8
ForlagSpringer
Publikationsdatookt. 2019
Sider32-39
ISBN (Elektronisk)978-3-030-32046-1
DOI
StatusUdgivet - okt. 2019
NavnLecture Notes in Computer Science
Vol/bind11807
ISSN0302-9743

Emneord

  • High-dimensional indexes
  • Extended Cluster Pruning (eCP)
  • Index maintenance strategy
  • Cost model
  • Multimedia collections

Fingeraftryk

Dyk ned i forskningsemnerne om 'Index Maintenance Strategy and Cost Model for Extended Cluster Pruning'. Sammen danner de et unikt fingeraftryk.

Citationsformater