Beagle : automated extraction and interpretation of visualizations from the web
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
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Format: | Thesis |
Language: | eng |
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Massachusetts Institute of Technology
2017
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Online Access: | http://hdl.handle.net/1721.1/112665 |
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author | Duan, Peitong |
author2 | Michael Stonebraker. |
author_facet | Michael Stonebraker. Duan, Peitong |
author_sort | Duan, Peitong |
collection | MIT |
description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. |
first_indexed | 2024-09-23T12:01:58Z |
format | Thesis |
id | mit-1721.1/112665 |
institution | Massachusetts Institute of Technology |
language | eng |
last_indexed | 2024-09-23T12:01:58Z |
publishDate | 2017 |
publisher | Massachusetts Institute of Technology |
record_format | dspace |
spelling | mit-1721.1/1126652019-04-12T22:55:01Z Beagle : automated extraction and interpretation of visualizations from the web Duan, Peitong Michael Stonebraker. 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. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted student-submitted PDF version of thesis. Includes bibliographical references (pages 71-74). In this paper, we present Beagle, an automated data collection system to mine the web for SVG-based visualization images, label them with their corresponding visualization type (i.e., bar, scatter, pie, etc.), and make them available as a queryable data store. The key idea behind Beagle is a new SVG-based classification design to more effectively label visualizations rendered in a browser. Furthermore, Beagle is designed from the ground up to be extendable and modifiable in a straightforward way, to anticipate when new artifacts appear on the web, such as new JavaScript libraries, new visualization types, and better browser support for SVG. We evaluated Beagle's classification techniques on multiple collections of SVG-based visualizations extracted from the web, and found that Beagle provides a significant boost in accuracy compared to existing classification techniques, across a wide variety of visualization types. by Peitong Duan. M. Eng. 2017-12-08T21:20:37Z 2017-12-08T21:20:37Z 2017 2017 Thesis http://hdl.handle.net/1721.1/112665 1014123603 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 74 pages application/pdf Massachusetts Institute of Technology |
spellingShingle | Electrical Engineering and Computer Science. Duan, Peitong Beagle : automated extraction and interpretation of visualizations from the web |
title | Beagle : automated extraction and interpretation of visualizations from the web |
title_full | Beagle : automated extraction and interpretation of visualizations from the web |
title_fullStr | Beagle : automated extraction and interpretation of visualizations from the web |
title_full_unstemmed | Beagle : automated extraction and interpretation of visualizations from the web |
title_short | Beagle : automated extraction and interpretation of visualizations from the web |
title_sort | beagle automated extraction and interpretation of visualizations from the web |
topic | Electrical Engineering and Computer Science. |
url | http://hdl.handle.net/1721.1/112665 |
work_keys_str_mv | AT duanpeitong beagleautomatedextractionandinterpretationofvisualizationsfromtheweb |