東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Understanding the Interactions Between Text and Visualizations.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Understanding the Interactions Between Text and Visualizations./
作者:	Kim, Dae Hyun.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	109 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
Contained By:	Dissertations Abstracts International83-09B.
標題:	Algorithms. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29003856
ISBN:	9798209788447

Understanding the Interactions Between Text and Visualizations.
Kim, Dae Hyun.

Understanding the Interactions Between Text and Visualizations. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 109 p.

Source: Dissertations Abstracts International, Volume: 83-09, Section: B.

Thesis (Ph.D.)--Stanford University, 2021.

This item must not be sold to any third party vendors.

Visualizations and text are commonly used together in various applications, ranging from communicative documents to interactive tools for analyzing and exploring data. However, much about the relationship between visualizations and text remains unexplored. This thesis specifically focuses on three problems related to communicating the connections between the two representations and ways to surface these connections to address the problems.We begin by asking how readers integrate information between visualizations and text when the two representations emphasize different aspects of the underlying data. Through a user study, we find that readers can miss information presented in the text because they rely more on the visualizations for their takeaways. Based on the study results, we provide guidelines for authoring effective visualization-text pairs that doubly emphasize intended aspects of the underlying data.Identifying references between visualizations and text, which are often also spatially separated, is a mentally taxing process. The cognitive burden disrupts the flow of reading as readers traverse back and forth between visualizations and text in an attempt to mentally link their contents. We present an interactive document reader that extends existing PDF documents based on automatically extracted references between visualizations and text. Specifically, it facilitates document reading by highlighting the references and dynamically positioning visualizations close to relevant text. Our user study shows that the interface helps readers integrate visualizations into their flow of reading by helping them identify references more quickly and more accurately.When using a natural language interface for visualizations, users are often not informed about how the system operated on a visualization based on its interpretation of a text query. This lack of transparency leads users to question the system because they cannot easily verify the correctness of its outputs. We present a chart question answering system that generates visual explanations that clarifies how it used an input question and a visualization to obtain an answer. A user study reveals that our visual explanations significantly improve transparency and achieve levels of trust close to human-generated explanations.

ISBN: 9798209788447Subjects--Topical Terms:

536374
Algorithms.

Understanding the Interactions Between Text and Visualizations.
LDR:03375nmm a2200325 4500 001 2345735
005 20220613063807.5
008 241004s2021 ||||||||||||||||| ||eng d
020 $a 9798209788447
035 $a (MiAaPQ)AAI29003856
035 $a (MiAaPQ)STANFORDxk655mq8748
035 $a AAI29003856
040 $a MiAaPQ $c MiAaPQ
100 1 $a Kim, Dae Hyun. $3 3684729
245 1 0 $a Understanding the Interactions Between Text and Visualizations.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 109 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
500 $a Advisor: Agrawala, Maneesh;Landay, James A. ;Setlur, Vidya.
502 $a Thesis (Ph.D.)--Stanford University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Visualizations and text are commonly used together in various applications, ranging from communicative documents to interactive tools for analyzing and exploring data. However, much about the relationship between visualizations and text remains unexplored. This thesis specifically focuses on three problems related to communicating the connections between the two representations and ways to surface these connections to address the problems.We begin by asking how readers integrate information between visualizations and text when the two representations emphasize different aspects of the underlying data. Through a user study, we find that readers can miss information presented in the text because they rely more on the visualizations for their takeaways. Based on the study results, we provide guidelines for authoring effective visualization-text pairs that doubly emphasize intended aspects of the underlying data.Identifying references between visualizations and text, which are often also spatially separated, is a mentally taxing process. The cognitive burden disrupts the flow of reading as readers traverse back and forth between visualizations and text in an attempt to mentally link their contents. We present an interactive document reader that extends existing PDF documents based on automatically extracted references between visualizations and text. Specifically, it facilitates document reading by highlighting the references and dynamically positioning visualizations close to relevant text. Our user study shows that the interface helps readers integrate visualizations into their flow of reading by helping them identify references more quickly and more accurately.When using a natural language interface for visualizations, users are often not informed about how the system operated on a visualization based on its interpretation of a text query. This lack of transparency leads users to question the system because they cannot easily verify the correctness of its outputs. We present a chart question answering system that generates visual explanations that clarifies how it used an input question and a visualization to obtain an answer. A user study reveals that our visual explanations significantly improve transparency and achieve levels of trust close to human-generated explanations.
590 $a School code: 0212.
650 4 $a Algorithms. $3 536374
650 4 $a Women. $3 531755
650 4 $a Keywords. $3 3560140
650 4 $a Crowdsourcing. $3 3377825
650 4 $a Hindus. $3 3684730
650 4 $a Natural language. $3 3562052
650 4 $a Computer science. $3 523869
650 4 $a Gender studies. $3 2122708
650 4 $a Language. $3 643551
690 $a 0984
690 $a 0733
690 $a 0679
710 2 $a Stanford University. $3 754827
773 0 $t Dissertations Abstracts International $g 83-09B.
790 $a 0212
791 $a Ph.D.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29003856