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
fDate :
June 27 2014-July 2 2014
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;
Conference_Titel :
Big Data (BigData Congress), 2014 IEEE International Congress on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4799-5056-0
DOI :
10.1109/BigData.Congress.2014.116