青少年
发表于 2025-3-30 11:10:10
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
发表于 2025-3-30 14:00:32
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
发表于 2025-3-30 17:29:10
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dandruff
发表于 2025-3-31 00:01:07
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BOLUS
发表于 2025-3-31 03:49:36
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渐强
发表于 2025-3-31 06:45:24
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我们的面粉
发表于 2025-3-31 11:51:00
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
发表于 2025-3-31 16:18:58
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
发表于 2025-3-31 19:20:59
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
发表于 2025-3-31 21:56:26
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