• DocumentCode
    3192620
  • Title

    Verbalizing time series data from a macroscopic viewpoint

  • Author

    Kobayashi, Ichiro

  • Author_Institution
    Grad. Sch. of Humanities & Sci., Ochanomizu Univ., Tokyo, Japan
  • fYear
    2012
  • fDate
    6-8 Aug. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Most data observed in our lives are time series data. So, we need a method to be able to access and easily utilize the data. As a representative method to realize it, visualization is widely used. On the other hand, as we see that there are many texts, e.g., newspaper articles reporting the trends on stock prices, foreign exchange rates, weather conditions, etc. Explaining time-series data with words is also widely used. With this background, in this study, we focus on explaining time series data with words and propose a method to verbalize time series data from a macroscopic viewpoint -which is that we aim to verbalize time series data by visually recognizing the shapes of a line chart of time series data. We apply our proposed method to verbalize stock price time series data and evaluate the results of generated texts.
  • Keywords
    data visualisation; pricing; shape recognition; stock markets; text analysis; time series; data utilization; data verbalization; data visualization; line chart; newspaper article; shape recognition; stock price time series data; text;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American
  • Conference_Location
    Berkeley, CA
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-2336-9
  • Electronic_ISBN
    pending
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2012.6291029
  • Filename
    6291029