Matches in SemOpenAlex for { <https://semopenalex.org/work/W2057058417> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W2057058417 endingPage "438" @default.
- W2057058417 startingPage "396" @default.
- W2057058417 abstract "Histograms and related synopsis structures are popular techniques for approximating data distributions. These have been successful in query optimization and a variety of applications, including approximate querying, similarity searching, and data mining, to name a few. Histograms were a few of the earliest synopsis structures proposed and continue to be used widely. The histogram construction problem is to construct the best histogram restricted to a space bound that reflects the data distribution most accurately under a given error measure.The histograms are used as quick and easy estimates. Thus, a slight loss of accuracy, compared to the optimal histogram under the given error measure, can be offset by fast histogram construction algorithms. A natural question arises in this context: Can we find a fast near optimal approximation algorithm for the histogram construction problem? In this article, we give the first linear time (1+ϵ)-factor approximation algorithms (for any ϵ > 0) for a large number of histogram construction problems including the use of piecewise small degree polynomials to approximate data, workloads, etc. Several of our algorithms extend to data streams.Using synthetic and real-life data sets, we demonstrate that in many scenarios the approximate histograms are almost identical to optimal histograms in quality and are significantly faster to construct." @default.
- W2057058417 created "2016-06-24" @default.
- W2057058417 creator A5017534381 @default.
- W2057058417 creator A5035257754 @default.
- W2057058417 creator A5049064713 @default.
- W2057058417 date "2006-03-01" @default.
- W2057058417 modified "2023-10-16" @default.
- W2057058417 title "Approximation and streaming algorithms for histogram construction problems" @default.
- W2057058417 cites W1964482959 @default.
- W2057058417 cites W1996784330 @default.
- W2057058417 cites W2005188603 @default.
- W2057058417 cites W2008931591 @default.
- W2057058417 cites W2016910265 @default.
- W2057058417 cites W2021850646 @default.
- W2057058417 cites W2028660080 @default.
- W2057058417 cites W2047424291 @default.
- W2057058417 cites W2053075747 @default.
- W2057058417 cites W2080745194 @default.
- W2057058417 cites W2110704543 @default.
- W2057058417 cites W2112452856 @default.
- W2057058417 cites W2122731071 @default.
- W2057058417 cites W2128869116 @default.
- W2057058417 cites W2137851997 @default.
- W2057058417 cites W2153329411 @default.
- W2057058417 cites W2163964823 @default.
- W2057058417 cites W2164363676 @default.
- W2057058417 cites W2171903035 @default.
- W2057058417 cites W4236656499 @default.
- W2057058417 cites W4242587584 @default.
- W2057058417 doi "https://doi.org/10.1145/1132863.1132873" @default.
- W2057058417 hasPublicationYear "2006" @default.
- W2057058417 type Work @default.
- W2057058417 sameAs 2057058417 @default.
- W2057058417 citedByCount "117" @default.
- W2057058417 countsByYear W20570584172012 @default.
- W2057058417 countsByYear W20570584172013 @default.
- W2057058417 countsByYear W20570584172014 @default.
- W2057058417 countsByYear W20570584172015 @default.
- W2057058417 countsByYear W20570584172016 @default.
- W2057058417 countsByYear W20570584172017 @default.
- W2057058417 countsByYear W20570584172018 @default.
- W2057058417 countsByYear W20570584172019 @default.
- W2057058417 countsByYear W20570584172020 @default.
- W2057058417 countsByYear W20570584172021 @default.
- W2057058417 countsByYear W20570584172022 @default.
- W2057058417 countsByYear W20570584172023 @default.
- W2057058417 crossrefType "journal-article" @default.
- W2057058417 hasAuthorship W2057058417A5017534381 @default.
- W2057058417 hasAuthorship W2057058417A5035257754 @default.
- W2057058417 hasAuthorship W2057058417A5049064713 @default.
- W2057058417 hasConcept C11413529 @default.
- W2057058417 hasConcept C115961682 @default.
- W2057058417 hasConcept C148764684 @default.
- W2057058417 hasConcept C154945302 @default.
- W2057058417 hasConcept C41008148 @default.
- W2057058417 hasConcept C53533937 @default.
- W2057058417 hasConceptScore W2057058417C11413529 @default.
- W2057058417 hasConceptScore W2057058417C115961682 @default.
- W2057058417 hasConceptScore W2057058417C148764684 @default.
- W2057058417 hasConceptScore W2057058417C154945302 @default.
- W2057058417 hasConceptScore W2057058417C41008148 @default.
- W2057058417 hasConceptScore W2057058417C53533937 @default.
- W2057058417 hasIssue "1" @default.
- W2057058417 hasLocation W20570584171 @default.
- W2057058417 hasOpenAccess W2057058417 @default.
- W2057058417 hasPrimaryLocation W20570584171 @default.
- W2057058417 hasRelatedWork W1974461541 @default.
- W2057058417 hasRelatedWork W2035772776 @default.
- W2057058417 hasRelatedWork W2135362013 @default.
- W2057058417 hasRelatedWork W2174708000 @default.
- W2057058417 hasRelatedWork W2386767533 @default.
- W2057058417 hasRelatedWork W2413420451 @default.
- W2057058417 hasRelatedWork W2547013153 @default.
- W2057058417 hasRelatedWork W932358710 @default.
- W2057058417 hasRelatedWork W1488906711 @default.
- W2057058417 hasRelatedWork W2584500696 @default.
- W2057058417 hasVolume "31" @default.
- W2057058417 isParatext "false" @default.
- W2057058417 isRetracted "false" @default.
- W2057058417 magId "2057058417" @default.
- W2057058417 workType "article" @default.