WSEAS Transactions on Environment and Development
Print ISSN: 1790-5079, E-ISSN: 2224-3496
Volume 14, 2018
A New Forecasting System Using the Latent Dirichlet Allocation (LDA) Topic Modeling Technique
Authors: , , ,
Abstract: Although the Delphi technique is often used to forecast promising future technologies, this method is difficult, time-consuming, and costly. As an alternative, the Latent Dirichlet Allocation (LDA) topic modeling technique can be used. Therefore, this study aimed to develop a science and technology trend forecasting system using the LDA topic modeling technique as a form of text mining. An empirical analysis of 13,618 abstracts regarding U.S. artificial intelligence (AI)-related patents was conducted, and the results of the analysis were verified based on changes in the frequency of related words within the AI topics. The trend analysis of the AI topics resulted in six hot technologies and six cold technologies. The results of the verification showed that 8 out of the 11 technologies matched (1 technology could not be verified). This study provides a foundation for engine design by helping develop engines that enable simple and low-cost technology forecasting and by suggesting an appropriate topic modeling technique. The study also makes an academic contribution by encouraging follow-up studies. Moreover, the developed forecasting system may be used as an automated forecasting engine to conduct tasks related to regional innovation.
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Keywords: Development of prediction systems, scientific technology trends, technological prediction, text mining, topic modeling, analysis of technological trends
Pages: 363-373
WSEAS Transactions on Environment and Development, ISSN / E-ISSN: 1790-5079 / 2224-3496, Volume 14, 2018, Art. #38