Titlebook: Similarity Search and Applications; 13th International C Shin‘ichi Satoh,Lucia Vadicamo,Rasmus Pagh Conference proceedings 2020 Springer Na

青少年

Metrics and Ambits and Sprawls, Oh MyA follow-up to my previous tutorial on metric indexing, this paper walks through the classic structures, placing them all in the context of the recently proposed . framework. The indexes are presented as configurations of a single, more general structure, all queried using the same search procedure.

Antecedent

Pivot Selection for Narrow Sketches by Optimization Algorithmstion candidates in similarity search. We propose a pivot selection method for narrow sketches with a length such as 16-bits by optimization algorithms with the accuracy of filtering itself as the objective function.

松软

dandruff

BOLUS

渐强

我们的面粉

Accelerating Metric Filtering by Improving Bounds on Estimated Distancesthe unknown distance with information about possible angles within triangles. We show that two lower bounds and one upper bound on each distance exist in case of limited angles. We analyse their filtering power and confirm high improvements of efficiency by experiments on several real-life datasets.

债务

Optimal Metric Search Is Equivalent to the Minimum Dominating Set Problem-based AESA, repeatedly selecting the pivot that eliminates the most of the remaining points. As an illustration, the AESA heuristic is adapted to downplay the role of previously eliminated points, yielding some modest performance improvements over the original, as well as its younger relative iAESA2.

Accord

Taking Advantage of Highly-Correlated Attributes in Similarity Queries with Missing Valuesxperimental results show that . outperforms imputation methods with different missing rates. . was up to . better than the competitors in quality when querying over incomplete tuples, reducing . the error of similarity searches over incomplete data, and being up to 30.8 times faster than the closest competitor.

僵硬