1 Citation (Scopus)

Abstract

Since many applications rely on time-based data, visualizing temporal data and helping experts explore large time series data sets are critical in many application domains. In this interactive system preview, we argue that time series often carry structural features that can, if efficiently identified and effectively visualized, help reduce visual overload and help the user quickly focus on the relevant portions of the data sets. Relying on this observation, we introduce a novel STFMap system, which includes four innovative query- and feature-driven time series data set visualization techniques: (a) segment-maps, (b) warp-maps, (c) stretch-maps, and (d) feature-maps. These rely on the salient temporal features of the time series and their alignments with respect to the given user query to help users explore the data set in a query-driven fashion.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
Pages2743-2745
Number of pages3
DOIs
StatePublished - 2012
Event21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: Oct 29 2012Nov 2 2012

Other

Other21st ACM International Conference on Information and Knowledge Management, CIKM 2012
CountryUnited States
CityMaui, HI
Period10/29/1211/2/12

Fingerprint

Time series
Visualization

Keywords

  • data exploration
  • time series data sets

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Candan, K., Rossini, R., Sapino, M. L., & Wang, X. (2012). STFMap: Query- and feature-driven visualization of large time series data sets. In ACM International Conference Proceeding Series (pp. 2743-2745) https://doi.org/10.1145/2396761.2398747

STFMap : Query- and feature-driven visualization of large time series data sets. / Candan, Kasim; Rossini, Rosaria; Sapino, Maria Luisa; Wang, Xiaolan.

ACM International Conference Proceeding Series. 2012. p. 2743-2745.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Candan, K, Rossini, R, Sapino, ML & Wang, X 2012, STFMap: Query- and feature-driven visualization of large time series data sets. in ACM International Conference Proceeding Series. pp. 2743-2745, 21st ACM International Conference on Information and Knowledge Management, CIKM 2012, Maui, HI, United States, 10/29/12. https://doi.org/10.1145/2396761.2398747
Candan K, Rossini R, Sapino ML, Wang X. STFMap: Query- and feature-driven visualization of large time series data sets. In ACM International Conference Proceeding Series. 2012. p. 2743-2745 https://doi.org/10.1145/2396761.2398747
Candan, Kasim ; Rossini, Rosaria ; Sapino, Maria Luisa ; Wang, Xiaolan. / STFMap : Query- and feature-driven visualization of large time series data sets. ACM International Conference Proceeding Series. 2012. pp. 2743-2745
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