@inproceedings{44787538279145c8af4c4f9114887a87,
title = "The Visualization of Innovation Pathway Based on Patent Data—Comparison Between Japan and America",
abstract = "Innovation trends are a crucial factor in determining one country{\textquoteright}s industrial development, and with the progress of modern machine learning technology, many are studying patent document analysis. People consider patents to contain important information for analyzing the innovation process, but patents contain much complicated jargon, and the methods for extracting information were limited. The authors applied the document analysis and visualization method newly proposed in the previous research and tried to compare the innovation process for patent documents as a whole within a certain period between Japan and the United States. As a result, we realized that in the 15 years, the topic vibration in Japan is more stable than in the US, and the contents in US patents are more concentrated than those in Japan.",
keywords = "Patents, Text mining, Visualization",
author = "Zhiyan Chen and Yusuke Matsumoto and Aiko Suge and Hiroshi Takahashi",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 15th International KES Conference on Agent and Multi-Agent Systems-Technologies and Applications, KES-AMSTA 2021 ; Conference date: 14-06-2021 Through 16-06-2021",
year = "2021",
doi = "10.1007/978-981-16-2994-5_22",
language = "English",
isbn = "9789811629938",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "265--273",
editor = "G. Jezic and J. Chen-Burger and M. Kusek and R. Sperka and Howlett, {R. J.} and Jain, {Lakhmi C.} and Jain, {Lakhmi C.} and Jain, {Lakhmi C.}",
booktitle = "Agents and Multi-Agent Systems",
}
