Understanding and controlling information propagation in multilayer networks

2023 Fiscal Year Final Research Report

• Project/Area Number: 17H01785
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Research Field: Intelligent informatics
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Murata Tsuyoshi 東京工業大学, 情報理工学院, 教授 (90242289)
• Project Period (FY): 2017-04-01 – 2022-03-31
• Keywords: 多層ネットワーク / 情報伝搬

Outline of Final Research Achievements

Preventing cascading disasters and spreading beneficial information through transportation networks such as railways, roads, and social media networks, is an urgent issue in the present social infrastructures. As for the achievements of this research project, papers have been accepted in academic journals such as ACM Transactions on Knowledge Discovery from Data, Future Generation Computer Systems, IEEE Access, and Information Science, and at some international conferences. Additionally, this research theme has also led to results in graph embedding and graph neural networks.

Free Research Field

知能情報学

Academic Significance and Societal Importance of the Research Achievements

本研究課題を契機として、グラフを対象とした深層学習についての研究に着手しており、グラフエンベディングやグラフニューラルネットワークにおける研究成果に結びついてきている。特に2022年にオーム社から出版した「グラフニューラルネットワーク: PyTorchによる実装」は、この分野における和書としては日本で最初のものであり、注目を集めた。