Visualizing database queries
Name
890154135-MIT.pdf
Description
Full printable version
Size
4.8 MB
Format
Adobe PDF
Checksum (MD5)
6fb1aa14188f898d3721a431ed763706
Author(s)
Vartak, Manasi
Advisor(s)
Samuel Madden.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
Data analysts operating on large volumes of data often rely on visualizations to interpret the results of queries. However, finding the right visualization for a query is a laborious and time-consuming task. We propose SEEDB, a system that partially automates this task: given a query, SEEDB explores the space of all possible visualizations, and automatically identifies and recommends to the analyst those visualizations it finds to be most "interesting" or "useful".
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
25
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 50-52).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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