Visualizing database queries

Author(s)
Vartak, Manasi
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Samuel Madden.
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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).
 
Date issued
2014
URI
http://hdl.handle.net/1721.1/90143
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.
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