Technology Development Strategy of Piggyback Transportation System Using Topic Modeling Based on LDA Algorithm

Sung-Chan Jun; Han seongho; KIM SANG BAEK

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2020, 25(12), pp.261-270
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Sung-Chan Jun ¹, Han seongho ², KIM SANG BAEK ³

¹고려대학교
²한국철도기술연구원
³연세대학교

ABSTRACT

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify “topics” that are corresponding to “key” technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these “key” technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the “key” promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.
KEYWORDS

Multi-modal, Piggyback flatcar system, Patent analysis, Network analysis, Time series analysis, Clustering
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