Charles Explorer logo
🇬🇧

NM-tree: Flexible Approximate Similarity Search in Metric and Non-metric Spaces

Publication at Faculty of Mathematics and Physics |
2008

Abstract

So far, an efficient similarity search in multimedia databases has been carried out by metric access methods (MAMs), where the utilized similarity measure had to satisfy the metric properties (reflexivity, non-negativity, symmetry, triangle inequality). Recently, the introduction of TriGen algorithm (turning any nonmetric into metric) enabled MAMs to perform also nonmetric similarity search.

Moreover, it simultaneously enabled faster approximate search (either metric or nonmetric). However, a simple application of TriGen as the first step before MAMs' indexing assumes a fixed ``approximation level'', that is, a user-defined tolerance of retrieval precision is preset for the whole index lifetime.

In this paper, we push the similarity search forward; we propose the NM-tree (nonmetric tree) -- a modification of M-tree which natively aggregates the TriGen algorithm to support \emph{flexible approximate} nonmetric or metric search.