The retrieval of objects from a multimedia database employs a measure which defines a similarity score for every pair of objects. The measure should effectively follow the nature of similarity, hence, it should not be limited by the triangular inequality, regarded as a restriction in similarity modeling. On the other hand, the retrieval should be as efficient (or fast) as possible. The measure is thus often restricted to a metric, because then the search can be handled by metric access methods (MAMs). In this paper we propose a general method of non-metric search by MAMs. We show the triangular inequality can be enforced for any semimetric (reflexive, non-negative and symmetric measure), resulting in a metric that preserves the original similarity orderings (retrieval effectiveness). We propose the TriGen algorithm for turning any black-box semimetric into (approximated) metric, just by use of distance distribution in a fraction of the database, The algorithm finds such a metric for which the retrieval efficiency is maximized, considering any MAM. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Skopal, T. (2006). On fast non-metric similarity search by metric access methods. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3896 LNCS, pp. 718–736). https://doi.org/10.1007/11687238_43
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