Technology changes with the times. It is difficult to predict, as technology develops under the influence of several factors. We analyze the technology by carrying out the patent from a time series perspective. The study consists of two phases. In the first phase, time series models detect the trend, cycle, and seasonality of the technology. Next phase performs to predict the importance of term. In order to confirm the practical applicability of the proposed method, 2,268 industrial robot patents were collected and tested. As a result, it was found that technologies beyond the dual control based on carbon materials among industrial robots will continue to develop.
Bibliographical noteFunding Information:
This research was supported by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea, under the Fostering Global Talents for Innovative Growth Program (P0008749) supervised by the Korea Institute for Advancement of Technology (KIAT).
© 2020 J. Adv. Inf. Technol.
- Patent analysis
- Predictive modeling
- Time series
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications
- Artificial Intelligence
- Computer Networks and Communications