Techniques for structured data discovery
Name
1102055969-MIT.pdf
Size
1.36 MB
Format
Adobe PDF
Checksum (MD5)
482ca08ad6f3edc395c9531623c47b4a
Author(s)
Fok, Lordique(Lordique S.)
Advisor(s)
Eran Egozy and David Andrzejewski.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
The discovery of structured data, or data that is tagged by key-value pairs, is a problem that can be subdivided into two issues: how best to structure information architecture and user interaction for discovery; and how to intelligently display data in a way that that optimizes the discovery of "useful" (i.e. relevant and helpful for a user's current use case) data. In this thesis, I investigate multiple methods of addressing both issues, and the results of evaluating these methods qualitatively and quantitatively. Specifically, I implement and evaluate: a novel interface design which combines different aspects of existing interfaces, two methods of diversifying data subsets given a search query, three methods of incorporating relevance in data subsets given a search query and information about the user's historic queries, a novel method of visualizing structured data, and two methods of inducing hierarchy on structured data in the presence of an partial data schema. These implementations and evaluations are shown to be effective in structuring information architecture and user interaction for structured data discovery, but are only partially effective in intelligently displaying data to optimize discovery of useful structured data.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 63-64).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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