• DocumentCode
    3280921
  • Title

    A feature selection method for comparision of each concept in big data

  • Author

    Nakanishi, Takafumi

  • Author_Institution
    Center for Global Commun. (GLOCOM), Int. Univ. of Japan, Tokyo, Japan
  • fYear
    2015
  • fDate
    June 28 2015-July 1 2015
  • Firstpage
    229
  • Lastpage
    234
  • Abstract
    In this paper, we present a new feature selection method for comparison of each event in big data. The method selects appropriate features for comparing or evaluating each event when we prepare an event set. There are massive data on the Internet as big data. We have been able to retrieve appropriate data sets from them by using given keywords. However, it is still difficult to use these data to compare some concepts. For example, when you would like to compare the difference between your company and a rival company, it is difficult to compare them, because evaluation axes are needed to compare them. This method extracts evaluation axes as features in a data-driven manner. We can compare them by using the extracted axes as the features. This means that the system automatically selects the appropriate features which we should focus on when we compare them.
  • Keywords
    Big Data; Internet; Internet; big data; data-driven manner; evaluation axes; feature selection method; keywords; massive data; rival company; Aggregates; Big data; Companies; Context; Estimation; Feature extraction; Internet; big data; context-dependent; data-driven; feature selection; semantic computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
  • Conference_Location
    Las Vegas, NV
  • Type

    conf

  • DOI
    10.1109/ICIS.2015.7166598
  • Filename
    7166598