Visual Exploration of Time-Series Forecasts through Structured Navigation
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Visual Exploration of Time-Series Forecasts through Structured Navigation. / Wang, Xiaoyi; Hornbæk, Kasper.
Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020. ed. / Genny Tortora; Giuliana Vitiello; Marco Winckler. Association for Computing Machinery, 2020. p. 1-9 38 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Visual Exploration of Time-Series Forecasts through Structured Navigation
AU - Wang, Xiaoyi
AU - Hornbæk, Kasper
PY - 2020
Y1 - 2020
N2 - Evaluating the forecasting ability of time-series involves observations of multiple charts representing different aspects of model accuracy. However, the sequence of the charts observed by users is not controlled and it is difficult for users to discover relations among charts. Therefore, we propose a method for constructing a navigation structure that shows these relations based on the syntax and semantics of the charts. An excerpt from the structure is used as a context menu that allows users to navigate through a series of charts and explore their relations in a structured way. A qualitative study is conducted to evaluate the system and the results show that our approach helps users explore the connections among charts and enhances the understanding of time-series forecasting performance.
AB - Evaluating the forecasting ability of time-series involves observations of multiple charts representing different aspects of model accuracy. However, the sequence of the charts observed by users is not controlled and it is difficult for users to discover relations among charts. Therefore, we propose a method for constructing a navigation structure that shows these relations based on the syntax and semantics of the charts. An excerpt from the structure is used as a context menu that allows users to navigate through a series of charts and explore their relations in a structured way. A qualitative study is conducted to evaluate the system and the results show that our approach helps users explore the connections among charts and enhances the understanding of time-series forecasting performance.
KW - model evaluation
KW - navigation
KW - time series
U2 - 10.1145/3399715.3399906
DO - 10.1145/3399715.3399906
M3 - Article in proceedings
AN - SCOPUS:85093068943
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 9
BT - Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020
A2 - Tortora, Genny
A2 - Vitiello, Giuliana
A2 - Winckler, Marco
PB - Association for Computing Machinery
T2 - 2020 International Conference on Advanced Visual Interfaces, AVI 2020
Y2 - 28 September 2020 through 2 October 2020
ER -
ID: 258325738