Paper Info
Title
Stft-Lda: An Algorithm To Facilitate The Visual Analysis Of Building Seismic Responses
Abstract
Civil engineers use numerical simulations of a building's responses to seismic forces to understand the nature of building failures, the limitations of building codes, and how to determine the latter to prevent the former. Such simulations generate large ensembles of multivariate, multiattribute time series. Comprehensive understanding of this data requires techniques that support the multivariate nature of the time series and can compare behaviors that are both periodic and non-periodic across multiple time scales and multiple time series themselves. In this paper, we present a novel technique to extract such patterns from time series generated from simulations of seismic responses. The core of our approach is the use of topic modeling, where topics correspond to interpretable and discriminative features of the earthquakes. We transform the raw time series data into a time series of topics, and use this visual summary to compare temporal patterns in earthquakes, query earthquakes via the topics across arbitrary time scales, and enable details on demand by linking the topic visualization with the original earthquake data. We show, through a surrogate task and an expert study, that this technique allows analysts to more easily identify recurring patterns in such time series. By integrating this technique in a prototype system, we show how it enables novel forms of visual interaction.
Year
DOI
Venue
2021
10.1177/14738716211038618
INFORMATION VISUALIZATION
Keywords
DocType
Volume
Visual data exploration, time series analysis
Journal
20
Issue
ISSN
Citations 
4
1473-8716
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Zhenge Zhao100.34
Danilo Motta200.34
Matthew S. Berger3203.67
Joshua A. Levine4445.79
Ismail B. Kuzucu500.34
Robert B. Fleischman600.34
Afonso Paiva700.34
Carlos Scheidegger800.34