Abstract
Bloom filter has been utilized in set representation and membership query. However, the algorithm is not quite suitable for representing multidimensional dataset. The paper presents a novel data structure based on Bloom filter for the multidimensional data representation. We further give the theoretical analysis and experimental evaluations of the algorithm. Results show that the algorithm can achieve the same false positive rate when dealing with exact membership queries. It can provide extra support of by-attribute membership query.
This work gives real world based experiments of our paper [1] published previously.
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Wang, Z., Luo, T. (2016). A Bloom Filter-Based Approach for Supporting the Representation and Membership Query of Multidimensional Dataset. In: Hung, P. (eds) Big Data Applications and Use Cases. International Series on Computer Entertainment and Media Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-30146-4_2
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DOI: https://doi.org/10.1007/978-3-319-30146-4_2
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