• DocumentCode
    682445
  • Title

    Data analysis and visualization using spectral decomposition and feature selection

  • Author

    Kamran, Arezoo ; Shamail, Shafay ; Awais, Mian M.

  • Author_Institution
    Dept. of Comput. Sci., Lahore Univ. of Manage. Sci. (LUMS), Lahore, Pakistan
  • fYear
    2013
  • fDate
    9-10 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The aim of this study is to develop a technique to mine time series data and extract patterns from it which help it to be visualized easily. These visualizations can be static or dynamic while showing the long term dominant trends in data and subduing the short term recurring features. The focus is on time series data from economics and business.
  • Keywords
    business data processing; data analysis; data mining; data visualisation; economics; time series; business data; data analysis; data visualization; dominant data trends; economics data; feature selection; pattern extraction; short term recurring features; spectral decomposition; time series data mining; Data mining; Data visualization; Discrete cosine transforms; Feature extraction; Market research; Time series analysis; Visualization; Data Mining; Data Visualization; Feature selection; Spectral Decomposition; Time Series Analysis; Trend Highlighting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies (ICET), 2013 IEEE 9th International Conference on
  • Conference_Location
    Islamabad
  • Print_ISBN
    978-1-4799-3456-0
  • Type

    conf

  • DOI
    10.1109/ICET.2013.6743528
  • Filename
    6743528
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=682445