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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1109/TVCG.2020.3030403
|2 doi
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| 028 |
5 |
2 |
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|a DE-627
|b ger
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|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Shi, Danqing
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Calliope
|b Automatic Visual Data Story Generation from a Spreadsheet
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| 264 |
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1 |
|c 2021
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Revised 02.02.2021
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| 500 |
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|a published: Print-Electronic
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| 500 |
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Visual data stories shown in the form of narrative visualizations such as a poster or a data video, are frequently used in data-oriented storytelling to facilitate the understanding and memorization of the story content. Although useful, technique barriers, such as data analysis, visualization, and scripting, make the generation of a visual data story difficult. Existing authoring tools rely on users' skills and experiences, which are usually inefficient and still difficult. In this paper, we introduce a novel visual data story generating system, Calliope, which creates visual data stories from an input spreadsheet through an automatic process and facilities the easy revision of the generated story based on an online story editor. Particularly, Calliope incorporates a new logic-oriented Monte Carlo tree search algorithm that explores the data space given by the input spreadsheet to progressively generate story pieces (i.e., data facts) and organize them in a logical order. The importance of data facts is measured based on information theory, and each data fact is visualized in a chart and captioned by an automatically generated description. We evaluate the proposed technique through three example stories, two controlled experiments, and a series of interviews with 10 domain experts. Our evaluation shows that Calliope is beneficial to efficient visual data story generation
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| 650 |
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4 |
|a Journal Article
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| 700 |
1 |
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|a Xu, Xinyue
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Sun, Fuling
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Shi, Yang
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cao, Nan
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 27(2021), 2 vom: 13. Feb., Seite 453-463
|w (DE-627)NLM098269445
|x 1941-0506
|7 nnns
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| 773 |
1 |
8 |
|g volume:27
|g year:2021
|g number:2
|g day:13
|g month:02
|g pages:453-463
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TVCG.2020.3030403
|3 Volltext
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|d 27
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|h 453-463
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