Techniques for structured data discovery

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.

Bibliographic Details
Main Author: Fok, Lordique(Lordique S.)
Other Authors: Eran Egozy and David Andrzejewski.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2019
Subjects:
Online Access:https://hdl.handle.net/1721.1/121671
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author Fok, Lordique(Lordique S.)
author2 Eran Egozy and David Andrzejewski.
author_facet Eran Egozy and David Andrzejewski.
Fok, Lordique(Lordique S.)
author_sort Fok, Lordique(Lordique S.)
collection MIT
description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
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spelling mit-1721.1/1216712019-08-07T03:03:09Z Techniques for structured data discovery Fok, Lordique(Lordique S.) Eran Egozy and David Andrzejewski. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. 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). 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. by Lordique Fok. M. Eng. M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2019-07-15T20:32:46Z 2019-07-15T20:32:46Z 2019 2019 Thesis https://hdl.handle.net/1721.1/121671 1102055969 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 64 pages application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Fok, Lordique(Lordique S.)
Techniques for structured data discovery
title Techniques for structured data discovery
title_full Techniques for structured data discovery
title_fullStr Techniques for structured data discovery
title_full_unstemmed Techniques for structured data discovery
title_short Techniques for structured data discovery
title_sort techniques for structured data discovery
topic Electrical Engineering and Computer Science.
url https://hdl.handle.net/1721.1/121671
work_keys_str_mv AT foklordiquelordiques techniquesforstructureddatadiscovery