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LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers

Publication ,  Conference
Miao, Z; Lee, A; Roy, S
Published in: Proceedings of the VLDB Endowment
January 1, 2018

In this demonstration, we will present LensXPlain, an interactive system to help users understand answers of aggregate queries by providing meaningful explanations. Given a SQL group-by query and a question from a user \why output o is high /low", or \why output o1 is higher/lower than o2", LensXPlain helps users explore the results and find subsets of tuples captured by predicates that contributed the most toward such observations. The contributions are measured either by intervention (if the contributing tuples are removed, the values or the ratios in the user question change in the opposite direction), or by aggravation (if the query is restricted to the contributing tuples, the observations change more in the same direction). LensXPlain uses ensemble learning for recommending useful attributes in explanations, and employs a suite of optimizations to enable explanation generation and refinement at an interactive speed. In the demonstration, the audience can run aggregation queries over real world datasets, browse the answers using a graphical user interface, ask questions on unexpected/interesting query results with simple visualizations, and explore and refine explanations returned by LensXPlain.

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Published In

Proceedings of the VLDB Endowment

DOI

EISSN

2150-8097

Publication Date

January 1, 2018

Volume

12

Issue

12

Start / End Page

1898 / 1901

Related Subject Headings

  • 4605 Data management and data science
  • 0807 Library and Information Studies
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics
 

Citation

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Miao, Z., Lee, A., & Roy, S. (2018). LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers. In Proceedings of the VLDB Endowment (Vol. 12, pp. 1898–1901). https://doi.org/10.14778/3352063.3352094
Miao, Z., A. Lee, and S. Roy. “LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers.” In Proceedings of the VLDB Endowment, 12:1898–1901, 2018. https://doi.org/10.14778/3352063.3352094.
Miao Z, Lee A, Roy S. LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers. In: Proceedings of the VLDB Endowment. 2018. p. 1898–901.
Miao, Z., et al. “LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers.” Proceedings of the VLDB Endowment, vol. 12, no. 12, 2018, pp. 1898–901. Scopus, doi:10.14778/3352063.3352094.
Miao Z, Lee A, Roy S. LensXPlain: Visualizing and explaining contributing subsets for aggregate query answers. Proceedings of the VLDB Endowment. 2018. p. 1898–1901.

Published In

Proceedings of the VLDB Endowment

DOI

EISSN

2150-8097

Publication Date

January 1, 2018

Volume

12

Issue

12

Start / End Page

1898 / 1901

Related Subject Headings

  • 4605 Data management and data science
  • 0807 Library and Information Studies
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics