Visual Exploration of Time-Series Forecasts through Structured Navigation

Xiaoyi Wang, Kasper Hornbæk

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

1 Citationer (Scopus)

Abstract

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.

OriginalsprogEngelsk
TitelProceedings of the Working Conference on Advanced Visual Interfaces, AVI 2020
RedaktørerGenny Tortora, Giuliana Vitiello, Marco Winckler
ForlagAssociation for Computing Machinery
Publikationsdato2020
Sider1-9
Artikelnummer38
ISBN (Elektronisk)9781450375351
DOI
StatusUdgivet - 2020
Begivenhed2020 International Conference on Advanced Visual Interfaces, AVI 2020 - Salerno, Italien
Varighed: 28 sep. 20202 okt. 2020

Konference

Konference2020 International Conference on Advanced Visual Interfaces, AVI 2020
Land/OmrådeItalien
BySalerno
Periode28/09/202002/10/2020
SponsorACM Special Interest Group on Computer-Human Interaction (SIGCHI), ACM Special Interest Group on Hypertext, Hypermedia, and Web (SIGWEB), ACM Special Interest Group on Multimedia (SIGMM), Association for Computing Machinery (ACM)
NavnACM International Conference Proceeding Series

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