Shape grammar extraction for efficient query-by-sketch pattern matching in long time series

Muthumanickam, Prithiviraj K.; Vrotsou, Katerina; Cooper, Matthew; Johansson, Jimmy

doi:10.1109/vast.2016.7883518

Cited by 17 publications

(19 citation statements)

References 48 publications

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“…In these systems, a user draws a pattern in the visualization and the system searches through the data to find data items that exhibit similar patterns. This technique has been demonstrated to work well for querying temporal [Wat01,CG16,MVCJ16] and spatial data [WCW * 14].…”

Section: Image Spacementioning

confidence: 99%

Survey on the Analysis of User Interactions and Visualization Provenance

Xu¹,

Ottley²,

Walchshofer³

et al. 2020

Preprint

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There is fast-growing literature on provenance-related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete picture of the current state of inquiry and identify knowledge gaps or possible avenues for further investigation. In this STAR, we aim to produce a comprehensive survey of work in the data visualization and visual analytics field that focus on the analysis of user interaction and provenance data. We structure our survey around three primary questions: (1) WHY analyze provenance data, (2) WHAT provenance data to encode and how to encode it, and (3) HOW to analyze provenance data. A concluding discussion provides evidence-based guidelines and highlights concrete opportunities for future development in this emerging area.

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Section: Image Spacementioning

confidence: 99%

Survey on the Analysis of User Interactions and Visualization Provenance

Xu¹,

Ottley²,

Walchshofer³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Others have studied designing user-driven contexts based on novel interactions. In particular, Muthumanickam et al 16 explore long time series by constructing a grammar of basic shapes based on user sketches. Correll and Gleicher 17 also study sketching for time series.…”

Section: Related Workmentioning

confidence: 99%

STFT-LDA: An algorithm to facilitate the visual analysis of building seismic responses

Zhao

Motta

Berger

et al. 2021

Information Visualization

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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.

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“…Later approaches focus on algorithmic similarity, for example through the automatic detection of specific "motifs", simple shapes such as spikes or sinks that users can combine to form queries [27]. Others [44] examine how to automatically extract a grammar to express time series approximately and simplify the search of matches to a sketched query, or they have focused on algorithmic performance and scalability of similarity search [69,70]. Recently, Qetch [41] presented a sketch-based querying system and a similarity algorithm that is scale independent.…”

Section: Time Series Similaritymentioning

confidence: 99%

Comparing Similarity Perception in Time Series Visualizations

Gogolou

Tsandilas

Palpanas

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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A common challenge faced by many domain experts working with time series data is how to identify and compare similar patterns. This operation is fundamental in high-level tasks, such as detecting recurring phenomena or creating clusters of similar temporal sequences. While automatic measures exist to compute time series similarity, human intervention is often required to visually inspect these automatically generated results. The visualization literature has examined similarity perception and its relation to automatic similarity measures for line charts, but has not yet considered if alternative visual representations, such as horizon graphs and colorfields, alter this perception. Motivated by how neuroscientists evaluate epileptiform patterns, we conducted two experiments that study how these three visualization techniques affect similarity perception in EEG signals. We seek to understand if the time series results returned from automatic similarity measures are perceived in a similar manner, irrespective of the visualization technique; and if what people perceive as similar with each visualization aligns with different automatic measures and their similarity constraints. Our findings indicate that horizon graphs align with similarity measures that allow local variations in temporal position or speed (i.e., dynamic time warping) more than the two other techniques. On the other hand, horizon graphs do not align with measures that are insensitive to amplitude and y-offset scaling (i.e., measures based on z-normalization), but the inverse seems to be the case for line charts and colorfields. Overall, our work indicates that the choice of visualization affects what temporal patterns we consider as similar, i.e., the notion of similarity in time series is not visualization independent.

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Shape grammar extraction for efficient query-by-sketch pattern matching in long time series

Cited by 17 publications

References 48 publications

Survey on the Analysis of User Interactions and Visualization Provenance

Survey on the Analysis of User Interactions and Visualization Provenance

STFT-LDA: An algorithm to facilitate the visual analysis of building seismic responses

Comparing Similarity Perception in Time Series Visualizations

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