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Database Theory — ICDT 2001 : 8th International Conference London, UK, January 4–6, 2001 Proceedings

Overview of attention for book
Cover of 'Database Theory — ICDT 2001 : 8th International Conference London, UK, January 4–6, 2001 Proceedings'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Expressive Power of SQL
  3. Altmetric Badge
    Chapter 2 Query Evaluation via Tree-Decompositions
  4. Altmetric Badge
    Chapter 3 Scalar Aggregation in FD-Inconsistent Databases
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    Chapter 4 On Decidability and Complexity of Description Logics with Uniqueness Constraints
  6. Altmetric Badge
    Chapter 5 Expressiveness Issues and Decision Problems for Active Database Event Queries
  7. Altmetric Badge
    Chapter 6 A Theory of Transactions on Recoverable Search Trees
  8. Altmetric Badge
    Chapter 7 Minimizing View Sets without Losing Query-Answering Power
  9. Altmetric Badge
    Chapter 8 Cost Based Data Dissemination in Broadcast Networks
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    Chapter 9 Parallelizing the Data Cube
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    Chapter 10 Asymptotically Optimal Declustering Schemes for Range Queries
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    Chapter 11 Flexible Data Cubes for Online Aggregation
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    Chapter 12 Mining for Empty Rectangles in Large Data Sets
  14. Altmetric Badge
    Chapter 13 FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies
  15. Altmetric Badge
    Chapter 14 Axiomatization of Frequent Sets
  16. Altmetric Badge
    Chapter 15 On Answering Queries in the Presence of Limited Access Patterns
  17. Altmetric Badge
    Chapter 16 The Dynamic Complexity of Transitive Closure Is in DynTC°
  18. Altmetric Badge
    Chapter 17 Query Languages for Constraint Databases: First-Order Logic, Fixed-Points, and Convex Hulls
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    Chapter 18 A Semi-monad for Semi-structured Data (ICDT Version)
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    Chapter 19 Algebraic Rewritings for Optimizing Regular Path Queries
  21. Altmetric Badge
    Chapter 20 Why and Where: A Characterization of Data Provenance
  22. Altmetric Badge
    Chapter 21 Subsumption for XML Types
  23. Altmetric Badge
    Chapter 22 Towards Aggregated Answers for Semistructured Data
  24. Altmetric Badge
    Chapter 23 Orthogonal Range Queries in OLAP
  25. Altmetric Badge
    Chapter 24 Reasoning about Summarizability in Heterogeneous Multidimensional Schemas
  26. Altmetric Badge
    Chapter 25 Estimating Range Queries Using Aggregate Data with Integrity Constraints: A Probabilistic Approach
  27. Altmetric Badge
    Chapter 26 Constraint-Based Clustering in Large Databases
  28. Altmetric Badge
    Chapter 27 On the Surprising Behavior of Distance Metrics in High Dimensional Space
  29. Altmetric Badge
    Chapter 28 On Optimizing Nearest Neighbor Queries in High-Dimensional Data Spaces
Attention for Chapter 20: Why and Where: A Characterization of Data Provenance
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
policy
1 policy source
patent
1 patent
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
384 Mendeley
citeulike
7 CiteULike
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Chapter title
Why and Where: A Characterization of Data Provenance
Chapter number 20
Book title
Database Theory — ICDT 2001
Published in
Lecture notes in computer science, October 2001
DOI 10.1007/3-540-44503-x_20
Book ISBNs
978-3-54-041456-8, 978-3-54-044503-6
Authors

Buneman, Peter, Khanna, Sanjeev, Wang-Chiew, Tan, Peter Buneman, Sanjeev Khanna, Tan Wang-Chiew, Wang-Chiew Tan

Editors

Bussche, Jan van den, Vianu, Victor

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 384 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 22 6%
United Kingdom 14 4%
Germany 5 1%
Spain 3 <1%
Italy 3 <1%
Australia 3 <1%
Netherlands 3 <1%
Ireland 2 <1%
Brazil 2 <1%
Other 11 3%
Unknown 316 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 119 31%
Researcher 65 17%
Student > Master 60 16%
Student > Doctoral Student 23 6%
Student > Bachelor 21 5%
Other 66 17%
Unknown 30 8%
Readers by discipline Count As %
Computer Science 280 73%
Engineering 22 6%
Social Sciences 10 3%
Business, Management and Accounting 6 2%
Physics and Astronomy 4 1%
Other 24 6%
Unknown 38 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2023.
All research outputs
#1,972,976
of 24,359,979 outputs
Outputs from Lecture notes in computer science
#328
of 8,154 outputs
Outputs of similar age
#1,693
of 44,023 outputs
Outputs of similar age from Lecture notes in computer science
#1
of 33 outputs
Altmetric has tracked 24,359,979 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,154 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 44,023 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.