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2014
DOI: 10.7838/jsebs.2014.19.3.051
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A Pilot Study on Applying Text Mining Tools to Analyzing Steel Industry Trends : A Case Study of the Steel Industry for the Company "P"

Abstract: It becomes more and more important for business survival to have the ability to predict the future with uncertainties increasing faster and faster. To predict the future, text mining tools are one of the main candidate other than traditional quantitative analyses, but those efforts are still at their infancy. This paper is to introduce one of those efforts using the case of company "P" in the steel industry. Even with only four month pilot studies, we found strong possibilities, if not testified robustly, to p… Show more

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Cited by 7 publications
(2 citation statements)
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“…In the method of using the occurrence frequency and the TF-IDF value, parts of the keywords are selected and analyzed by evaluating the importance of the keyword without using all the keywords appearing in the document. Kim et al [26] and Min et al [27] selected future promising areas by analyzing the time series of words appearing in papers, news, and policy research reports. Choi et al [2] predicted promising technologies by investigating the network of keywords.…”
Section: Text Miningmentioning
confidence: 99%
“…In the method of using the occurrence frequency and the TF-IDF value, parts of the keywords are selected and analyzed by evaluating the importance of the keyword without using all the keywords appearing in the document. Kim et al [26] and Min et al [27] selected future promising areas by analyzing the time series of words appearing in papers, news, and policy research reports. Choi et al [2] predicted promising technologies by investigating the network of keywords.…”
Section: Text Miningmentioning
confidence: 99%
“…Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research: the information and communications technology industry (Chung and Lee, 2012), the construction industry (Jeong and Kim, 2012; Korea Institute of science and technology Evaluation and Planning, 2010), the steel industry (Min et al, 2014), the public sector (Korea Agency for Infrastructure Technology Advancement, 2013; Korea Institute of S&T Evaluation and Planning, 2014). There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner.…”
Section: Introductionmentioning
confidence: 99%