@inproceedings{b4dc8b0600e245c8b1aeebeb1289c9a4,
title = "Constructing a Decision-Making System Using Patent Document Analysis",
abstract = "In this study, we propose a new system to support corporate decision-making using patent documents. For R&D-oriented pharmaceutical companies, the creation of new drugs is indispensable for survival, and patents, the source of R&D, are an important factor in the creation of new drugs. In this study, we attempted to clarify the quantification of technical information in pharmaceutical companies by vectorizing the patent database DWPI using Sparse Composite Document Vectors (SCDV) for pharmaceutical companies in Japan. As a result of the analysis, we found the possibility of considering the strategy of pharmaceutical companies by visualizing patent documents.",
keywords = "Patent, Pharmaceutical company sparse composite document vectors, Strategy, Technology",
author = "Takashi Yonemura 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_23",
language = "English",
isbn = "9789811629938",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "275--283",
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",
}