ITU

Index Maintenance Strategy and Cost Model for Extended Cluster Pruning

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

Standard

Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. / Højsgaard, Anders Munck; Jónsson, Björn Thór; Bonnet, Philippe.

Proceedings of the International Conference on Similarity Search and Applications (SISAP). Springer, 2019. p. 32-39 (Lecture Notes in Computer Science, Vol. 11807).

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

Harvard

Højsgaard, AM, Jónsson, BT & Bonnet, P 2019, Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. in Proceedings of the International Conference on Similarity Search and Applications (SISAP). Springer, Lecture Notes in Computer Science, vol. 11807, pp. 32-39. https://doi.org/10.1007%2F978-3-030-32047-8_3

APA

Højsgaard, A. M., Jónsson, B. T., & Bonnet, P. (2019). Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. In Proceedings of the International Conference on Similarity Search and Applications (SISAP) (pp. 32-39). Springer. Lecture Notes in Computer Science, Vol.. 11807 https://doi.org/10.1007%2F978-3-030-32047-8_3

Vancouver

Højsgaard AM, Jónsson BT, Bonnet P. Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. In Proceedings of the International Conference on Similarity Search and Applications (SISAP). Springer. 2019. p. 32-39. (Lecture Notes in Computer Science, Vol. 11807). https://doi.org/10.1007%2F978-3-030-32047-8_3

Author

Højsgaard, Anders Munck ; Jónsson, Björn Thór ; Bonnet, Philippe. / Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. Proceedings of the International Conference on Similarity Search and Applications (SISAP). Springer, 2019. pp. 32-39 (Lecture Notes in Computer Science, Vol. 11807).

Bibtex

@inproceedings{1493d2f7c37543d5bdbb0910b2057aaf,
title = "Index Maintenance Strategy and Cost Model for Extended Cluster Pruning",
abstract = "With today{\textquoteright}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. ",
author = "H{\o}jsgaard, {Anders Munck} and J{\'o}nsson, {Bj{\"o}rn Th{\'o}r} and Philippe Bonnet",
year = "2019",
month = oct
doi = "10.1007%2F978-3-030-32047-8_3",
language = "English",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "32--39",
booktitle = "Proceedings of the International Conference on Similarity Search and Applications (SISAP)",
address = "Germany",

}

RIS

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 -

ID: 84765159