Emerging Technology Forecasting Using New Patent Information Analysis
Sunghae Jun, Seungjoo Lee
Abstract
Sunghae Jun, Seungjoo Lee
Abstract
Emerging technology drives technological development and innovation in diverse fields of technology. Emerging technology forecasting can predict the possible areas of emerging technology. However, it is difficult to forecast the emerging technology because most technology forecasting tasks depend on the subjective experience of experts. Patent analysis is an objective method to recognize the trends in technological development. Many patent analysis methods have been researched; these methods apply text mining techniques to analyze the text data of patent documents such as the title and abstract. This approach has some limitations, namely the computing cost and information loss associated with the preprocessing step of text mining. Therefore, we propose a new patent information analysis to overcome these problems. Using the International Patent Classification codes from the patent documents of a target technology, we construct an emerging technology forecasting model. This research combines statistical inference and neural networks to construct our model for new patent information analysis. We perform a case study to verify how our research can be practically applied, using nanotechnology as the target technology. Therefore, we contribute this research to R&D planning.
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Emerging technology drives technological development and innovation in diverse fields of technology. Emerging technology forecasting can predict the possible areas of emerging technology. However, it is difficult to forecast the emerging technology because most technology forecasting tasks depend on the subjective experience of experts. Patent analysis is an objective method to recognize the trends in technological development. Many patent analysis methods have been researched; these methods apply text mining techniques to analyze the text data of patent documents such as the title and abstract. This approach has some limitations, namely the computing cost and information loss associated with the preprocessing step of text mining. Therefore, we propose a new patent information analysis to overcome these problems. Using the International Patent Classification codes from the patent documents of a target technology, we construct an emerging technology forecasting model. This research combines statistical inference and neural networks to construct our model for new patent information analysis. We perform a case study to verify how our research can be practically applied, using nanotechnology as the target technology. Therefore, we contribute this research to R&D planning.
Key concepts: Patent visualisation, Patent analysis, Construct (python library), Data science, Computer science, Technology forecasting, Inference, Emerging technologies