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BMF: An Indexing Structure to Support Multi-element Check

机译:BMF:支持多元素检查的索引结构

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Standard Bloom Filter is an efficient structure to check element membership with low space cost and low false positive rate. However, the standard Bloom Filter assumes that all elements belong to a single set. When given multiple sets of elements, it cannot efficiently check whether or not multiple input elements belong to the same set, called multi-element check. To support the multi-element check, in this paper, we design a new data structure, namely Bloom Multi-filter (BMF). BMF maintains an array of integer numbers to support (1) the insertion of multiple sets of elements into BMF and (2) the lookup to answer multi-element check. We propose four techniques to improve the BMF and optimize the false positive rate. We conducted intensive experiments to study the tradeoff between BMF's space cost and lookup precision. Our experimental results indicate that BMF greatly outperforms the standard bloom filters with around 9.82 folds of lower false positive rate.
机译:标准绽放过滤器是一种有效的结构,用于检查具有低空间成本和低误率的元素成员资格。但是,标准绽放过滤器假定所有元素属于单个集。当给定多组元素时,它无法有效地检查多个输入元素是否属于同一组,称为多元素检查。为了支持多元素检查,请在本文中,我们设计一个新的数据结构,即绽放多滤波器(BMF)。 BMF维护一个整数数字数组,以支持(1)将多组元素插入BMF和(2)查找以应答多元素检查。我们提出了四种技术来改善BMF并优化假阳性率。我们进行了密集的实验,以研究BMF的空间成本与查找精度之间的权衡。我们的实验结果表明,BMF大大优于标准绽放过滤器,较低误差率约9.82倍。

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