Conference Paper/Proceeding/Abstract 13252 views 265 downloads
The Turing Test for Graph Drawing Algorithms
Helen C. Purchase 
,
Daniel Archambault ,
Stephen Kobourov ,
Martin Nöllenburg ,
Sergey Pupyrev ,
Hsiang-Yun Wu
,
Daniel Archambault ,
Stephen Kobourov ,
Martin Nöllenburg ,
Sergey Pupyrev ,
Hsiang-Yun Wu
Lecture Notes in Computer Science, Volume: 12590, Pages: 466 - 481
Swansea University Author:
Daniel Archambault
-
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DOI (Published version): 10.1007/978-3-030-68766-3_36
Abstract
Do algorithms for drawing graphs pass the Turing Test? That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on `small' graphs, of a size for which it would be reasonable for someone to choose to draw the...
| Published in: | Lecture Notes in Computer Science |
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| ISBN: | 9783030687656 9783030687663 |
| ISSN: | 0302-9743 1611-3349 |
| Published: |
Cham
Springer International Publishing
2021
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa55001 |
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| Abstract: |
Do algorithms for drawing graphs pass the Turing Test? That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on `small' graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing algorithms, although this is not always the case for graphs drawn by force-directed or multi-dimensional scaling algorithms, making these good candidates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm. |
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| Keywords: |
Empirical studies, Graph Drawing Algorithms, Turing Test |
| College: |
Faculty of Science and Engineering |
| Start Page: |
466 |
| End Page: |
481 |