TY - GEN
T1 - Index Maintenance Strategy and Cost Model for Extended Cluster Pruning
AU - Højsgaard, Anders Munck
AU - Jónsson, Björn Thór
AU - Bonnet, Philippe
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
U2 - 10.1007%2F978-3-030-32047-8_3
DO - 10.1007%2F978-3-030-32047-8_3
M3 - Article in proceedings
T3 - Lecture Notes in Computer Science
SP - 32
EP - 39
BT - Proceedings of the International Conference on Similarity Search and Applications (SISAP)
PB - Springer
ER -