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  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

Discovering Interdisciplinary Convergence Technologies Using Content Analysis Technique Based on Topic Modeling

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2018, v.35 no.3, pp.77-100
https://doi.org/10.3743/KOSIM.2018.35.3.077


Abstract

The objectives of this study is to present a discovering process of interdisciplinary convergence technology using text mining of big data. For the convergence research of biotechnology(BT) and information communications technology (ICT), the following processes were performed. (1) Collecting sufficient meta data of research articles based on BT terminology list. (2) Generating intellectual structure of emerging technologies by using a Pathfinder network scaling algorithm. (3) Analyzing contents with topic modeling. Next three steps were also used to derive items of BT-ICT convergence technology. (4) Expanding BT terminology list into superior concepts of technology to obtain ICT-related information from BT. (5) Automatically collecting meta data of research articles of two fields by using OpenAPI service. (6) Analyzing contents of BT-ICT topic models. Our study proclaims the following findings. Firstly, terminology list can be an important knowledge base for discovering convergence technologies. Secondly, the analysis of a large quantity of literature requires text mining that facilitates the analysis by reducing the dimension of the data. The methodology we suggest here to process and analyze data is efficient to discover technologies with high possibility of interdisciplinary convergence.

keywords
융합기술, 유망기술, 지적구조, 토픽 모델링, 내용분석, convergence technology, emerging technology, intellectual structure, topic modeling, content analysis

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