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.
CITATION STYLE
Højsgaard, A. M., Jónsson, B. Þ., & Bonnet, P. (2019). Index Maintenance Strategy and Cost Model for Extended Cluster Pruning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11807 LNCS, pp. 32–39). Springer. https://doi.org/10.1007/978-3-030-32047-8_3
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