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Understanding and controlling information propagation in multilayer networks

Research Project

Project/Area Number 17H01785
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionTokyo 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
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥16,250,000 (Direct Cost: ¥12,500,000、Indirect Cost: ¥3,750,000)
Fiscal Year 2021: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2020: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2019: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2018: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2017: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Keywords多層ネットワーク / 情報伝搬 / コミュニティ / ネットワークエンベディング / ネットワーク / 影響最大化 / 変分オートエンコーダ / コミュニティ抽出 / 人工知能 / アルゴリズム
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.

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。

Report

(6 results)
  • 2023 Final Research Report ( PDF )
  • 2021 Annual Research Report
  • 2020 Annual Research Report
  • 2019 Annual Research Report
  • 2018 Annual Research Report
  • 2017 Annual Research Report
  • Research Products

    (15 results)

All 2021 2020 2019 2018 2017

All Journal Article (11 results) (of which Int'l Joint Research: 3 results,  Peer Reviewed: 11 results,  Open Access: 7 results) Presentation (3 results) (of which Int'l Joint Research: 3 results) Book (1 results)

  • [Journal Article] PGRA: Projected graph relation-feature attention network for heterogeneous information network embedding2021

    • Author(s)
      Chairatanakul Nuttapong、Liu Xin、Murata Tsuyoshi
    • Journal Title

      Information Sciences

      Volume: 570 Pages: 769-794

    • DOI

      10.1016/j.ins.2021.04.070

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Predicting Emergency Medical Service Demand With Bipartite Graph Convolutional Networks2021

    • Author(s)
      Jin Ruidong、Xia Tianqi、Liu Xin、Murata Tsuyoshi、Kim Kyoung-Sook
    • Journal Title

      IEEE Access

      Volume: 9 Pages: 9903-9915

    • DOI

      10.1109/access.2021.3050607

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Graph convolutional networks for graphs containing missing features2021

    • Author(s)
      Taguchi Hibiki、Liu Xin、Murata Tsuyoshi
    • Journal Title

      Future Generation Computer Systems

      Volume: 117 Pages: 155-168

    • DOI

      10.1016/j.future.2020.11.016

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Graph Neural Networks for Fast Node Ranking Approximation2021

    • Author(s)
      Sunil Maurya, Liu Xin, Tsuyoshi Murata
    • Journal Title

      ACM Transactions on Knowledge Discovery from Data

      Volume: 15 Issue: 5 Pages: 1-32

    • DOI

      10.1145/3446217

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Graph Convolutional Network with Time-based Mini-batch for Information Diffusion Prediction2020

    • Author(s)
      Hajime Miyazawa, Tsuyoshi Murata
    • Journal Title

      The 9th International Conference on Complex Networks and their Applications (Complex Networks 2020)

      Volume: 944 Pages: 8376-8383

    • DOI

      10.1007/978-3-030-65351-4_5

    • ISBN
      9783030653507, 9783030653514
    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Embedding of Signed Networks Focusing on Both Structure and Relation2020

    • Author(s)
      Tsuyoshi Murata, Hiroki Arihara
    • Journal Title

      the 11th International Conference on Complex Networks (CompleNet 2020)

      Volume: 1 Pages: 60-69

    • DOI

      10.1007/978-3-030-40943-2_6

    • ISBN
      9783030409425, 9783030409432
    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Semi-supervised Learning on Network Using Structure Features and Graph Convolution2019

    • Author(s)
      立花誠人,村田剛志
    • Journal Title

      Transactions of the Japanese Society for Artificial Intelligence

      Volume: 34 Issue: 5 Pages: B-IC2_1-8

    • DOI

      10.1527/tjsai.B-IC2

    • NAID

      130007700226

    • ISSN
      1346-0714, 1346-8030
    • Year and Date
      2019-09-01
    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Fast Approximations of Betweenness Centrality with Graph Neural Networks2019

    • Author(s)
      Maurya Sunil Kumar、Liu Xin、Murata Tsuyoshi
    • Journal Title

      Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM’19)

      Volume: - Pages: 2149-2152

    • DOI

      10.1145/3357384.3358080

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Extended Methods for Influence Maximization in Dynamic Networks2018

    • Author(s)
      Tsuyoshi Murata, Hokuto Koga
    • Journal Title

      Computational Social Networks

      Volume: Vol.5, No.8 Issue: 1 Pages: 1-21

    • DOI

      10.1186/s40649-018-0056-8

    • Related Report
      2018 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Constrained Community Detection in Multiplex Networks2017

    • Author(s)
      Eguchi Koji、Murata Tsuyoshi
    • Journal Title

      Social Informatics (Proceedings of SocInfo 2017)

      Volume: 1 Pages: 75-87

    • DOI

      10.1007/978-3-319-67217-5_6

    • ISBN
      9783319672168, 9783319672175
    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Methods for Influence Maximization in Dynamic Networks2017

    • Author(s)
      Murata Tsuyoshi、Koga Hokuto
    • Journal Title

      Complex Networks & Their Applications VI (Proceedings of Complex Networks 2017)

      Volume: 1 Pages: 955-966

    • DOI

      10.1007/978-3-319-72150-7_77

    • ISBN
      9783319721491, 9783319721507
    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Presentation] Learning Community Structure with Variational Autoencoder2018

    • Author(s)
      Jun Jin Choong, Xin Liu, Tsuyoshi Murata
    • Organizer
      IEEE International Conference on Data Mining (ICDM 2018)
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Flow-Aware Vertex Protection Strategy on Large Social Networks2017

    • Author(s)
      Arie Wahyu Wijayanto, Tsuyoshi Murata
    • Organizer
      The 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Motif-Aware Graph Embedding2017

    • Author(s)
      Hoang Nguyen, Tsuyoshi Murata
    • Organizer
      The Third International Workshop on Representation Learning for Graphs (ReLiG 2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research
  • [Book] Pythonで学ぶネットワーク分析 ColaboratoryとNetworkXを使った実践入門2019

    • Author(s)
      村田剛志
    • Total Pages
      192
    • Publisher
      オーム社
    • ISBN
      9784274224256
    • Related Report
      2019 Annual Research Report

URL: 

Published: 2017-04-28   Modified: 2025-01-30  

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