Timeseer: Detecting interesting distributions in multiple time series data

Tuan Nhon Dang, Leland Wilkinson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Widespread interest in features and trends in time series has generated a need for interactive tools that support discovering unusual events in time series. In this paper, we introduce an application (TimeSeer) for guiding interactive exploration through high-dimensional data. Our application is designed to handle the types of doubly-multivariate data series by working directly on noteworthy features such as density, skewness, shape, outliers, and texture.

Original languageEnglish
Title of host publicationVINCI 2012 - 5th International Symposium on Visual Information Communication and Interaction
Pages43-51
Number of pages9
DOIs
StatePublished - 2012
Event5th International Symposium on Visual Information Communication and Interaction, VINCI 2012 - Hangzhou, China
Duration: Sep 27 2012Sep 28 2012

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Symposium on Visual Information Communication and Interaction, VINCI 2012
CountryChina
CityHangzhou
Period09/27/1209/28/12

Keywords

  • scagnostics
  • scatterplot
  • time serie visualization

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