Index Maintenance Strategy and Cost Model for Extended Cluster Pruning

Anders Munck Højsgaard, Björn Thór Jónsson, Philippe Bonnet

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Similarity Search and Applications (SISAP)
Number of pages8
Publication dateOct 2019
ISBN (Electronic)978-3-030-32046-1
Publication statusPublished - Oct 2019
SeriesLecture Notes in Computer Science


Dive into the research topics of 'Index Maintenance Strategy and Cost Model for Extended Cluster Pruning'. Together they form a unique fingerprint.

Cite this