Similarity Search: The Metric Space Approach (Advances in Database Systems)

By P. Zezula, Giuseppe Amato, Vlastislav Dohnal, Michal Batko. 2005

979 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search (2021, background): “The larger the δ (x,y), the more dissimilar x and y are, and the closer to zero, the more similar they are [101].”
Distance based similarity models for content based multimedia retrieval (2013, background): “The tuple (X, δ) becomes a metric space [Chávez et al., 2001, Samet, 2006, Zezula et al., 2006] if δ is a metric distance function.”
Permutation Search Methods are Efficient, Yet Faster Search is Possible (2015, background): “, the triangle inequality [35, 45] or its generalization for non-metric spaces [21].”
Effective Proximity Retrieval by Ordering Permutations (2008, unknown): “Ç”
Engineering Efficient and Effective Non-metric Space Library (2013, background): “[40] (see also a survey by Chávez et al.”
Learning to Prune in Metric and Non-Metric Spaces (2013, background): “A comprehensive review of these approaches can be found in books by Zezula et al. [32] and Samet [27].”
Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions (2007, methodology): “One of techniques to transform asymmetric distances into symmetric form utilizes the addition method; d sym ( P , Q )= d asym ( P , Q ) + d asym ( Q , P ), e.g., The eqn (47) is d AdChi ( P , Q ) = d P ( P , Q ) + d P ( Q , P ) [2,3].”