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https://doi.org/10.1137/1.9781...
Article . 2008 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2007
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Bloom maps

Authors: Talbot, David; Talbot, John;
Abstract

We consider the problem of succinctly encoding a static map to support approximate queries. We derive upper and lower bounds on the space requirements in terms of the error rate and the entropy of the distribution of values over keys: our bounds differ by a factor log e. For the upper bound we introduce a novel data structure, the Bloom map, generalising the Bloom filter to this problem. The lower bound follows from an information theoretic argument.

15 pages

Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Computer Science - Data Structures and Algorithms, E.4, Data Structures and Algorithms (cs.DS)

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
bronze