• DocumentCode
    249507
  • Title

    Constructing an Issue Network from the Perspective of Common R&D Keywords

  • Author

    Namgyu Kim ; Shun, William Wong Xiu ; Jieun Kim ; Kee-Young Kwahk ; Seungryul Jeong ; Hyunchul Ahn

  • Author_Institution
    Grad. Sch. of Bus. IT, Kookmin Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    772
  • Lastpage
    773
  • Abstract
    The demand for extracting keywords related to national issues from various sources and using them to retrieve R&D information has increased rapidly recently. In order to satisfy this demand, three methodologies are proposed in this study: a hybrid methodology for extracting and integrating national issue keywords, a methodology for packaging R&D information that corresponds to national issues, and a methodology for generating an associative issue network related to relevant R&D information. Data analysis techniques, such as text mining, social network analysis, and association rules mining, are utilized to establish these methodologies.
  • Keywords
    data analysis; data mining; social sciences computing; text analysis; R&D information packaging; R&D keywords; association rules mining; associative issue network; data analysis techniques; issue network construction; national issue keyword extraction; national issue keyword integration; social network analysis; text mining; Association rules; Business; Industries; Packaging; Silver; Social network services; Association Rules Mining; Keyword Matching; National Issue Keywords; Social Network Analysis; Text Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2014 IEEE International Congress on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5056-0
  • Type

    conf

  • DOI
    10.1109/BigData.Congress.2014.116
  • Filename
    6906860