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Complex Networks & Their Applications XII

Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023 Volume 1

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Hocine Cherifi

    1. University of Burgundy, Dijon Cedex, France

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  2. Luis M. Rocha

    1. Thomas J. Watson College of Engineering and Applied Sciences, Binghamton University, Binghamton, USA

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  3. Chantal Cherifi

    1. IUT Lumière - Université Lyon 2, University of Lyon, Bron, France

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  4. Murat Donduran

    1. Department of Economics, Yildiz Technical University, Istanbul, Türkiye

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  • Presents the latest research in Complex Networks and their Applications
  • Gathers the edited proceedings of the Twelfth International Workshop on Complex Networks & their Applications
  • Offers state-of-the-art research on complex networks, including various research directions

Part of the book series: Studies in Computational Intelligence (SCI, volume 1141)

Included in the following conference series:

Conference proceedings info: COMPLEX NETWORKS 2023.

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Table of contents (38 papers)

  1. Front Matter

    Pages i-xxii
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  2. Graph Neural Networks

    1. Front Matter

      Pages 1-1
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    2. Network Design Through Graph Neural Networks: Identifying Challenges and Improving Performance

      • Donald Loveland, Rajmonda Caceres
      Pages 3-15

    3. Sparse Graph Neural Networks with Scikit-Network

      • Simon Delarue, Thomas Bonald
      Pages 16-24

    4. Enhancing Time Series Analysis with GNN Graph Classification Models

      • Alex Romanova
      Pages 25-36

    5. When Do We Need Graph Neural Networks for Node Classification?

      • Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Doina Precup
      Pages 37-48

    6. Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks

      • Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup
      Pages 49-60

    7. E-MIGAN: Tackling Cold-Start Challenges in Recommender Systems

      • Ahlem Drif, Hocine Cherifi
      Pages 61-73

    8. Heterophily-Based Graph Neural Network for Imbalanced Classification

      • Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
      Pages 74-86

    9. TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting

      • Nancy Xu, Chrysoula Kosma, Michalis Vazirgiannis
      Pages 87-99

    10. UnboundAttack: Generating Unbounded Adversarial Attacks to Graph Neural Networks

      • Sofiane Ennadir, Amr Alkhatib, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström
      Pages 100-111

    11. Uncertainty in GNN Learning Evaluations: The Importance of a Consistent Benchmark for Community Detection

      • William Leeney, Ryan McConville
      Pages 112-123

  3. Link Analysis and Ranking

    1. Front Matter

      Pages 125-125
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    2. Stochastic Degree Sequence Model with Edge Constraints (SDSM-EC) for Backbone Extraction

      • Zachary P. Neal, Jennifer Watling Neal
      Pages 127-136

    3. Minority Representation and Relative Ranking in Sampling Attributed Networks

      • Nelson Antunes, Sayan Banerjee, Shankar Bhamidi, Vladas Pipiras
      Pages 137-149

    4. A Framework for Empirically Evaluating Pretrained Link Prediction Models

      • Emilio Sánchez Olivares, Hanjo D. Boekhout, Akrati Saxena, Frank W. Takes
      Pages 150-161

    5. Masking Language Model Mechanism with Event-Driven Knowledge Graphs for Temporal Relations Extraction from Clinical Narratives

      • Kanimozhi Uma, Sumam Francis, Marie-Francine Moens
      Pages 162-174

  4. Machine Learning and Networks

    1. Front Matter

      Pages 175-175
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    2. Efficient Approach for Patient Monitoring: ML-Enabled Framework with Smart Connected Systems

      • G. Dheepak
      Pages 177-188

    3. Economic and Health Burdens of HIV and COVID-19: Insights from a Survey of Underserved Communities in Semi-Urban and Rural Illinois

      • John Matta, Koushik Sinha, Cameron Woodard, Zachary Sappington, John Philbrick
      Pages 189-201
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Other volumes

  1. Complex Networks & Their Applications XII

  2. Complex Networks & Their Applications XII

  3. Complex Networks & Their Applications XII

  4. Complex Networks & Their Applications XII

Keywords

About this book

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2023). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics and spreading processes; machine learning and graph neural networks as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.

Editors and Affiliations

  • University of Burgundy, Dijon Cedex, France

    Hocine Cherifi

  • Thomas J. Watson College of Engineering and Applied Sciences, Binghamton University, Binghamton, USA

    Luis M. Rocha

  • IUT Lumière - Université Lyon 2, University of Lyon, Bron, France

    Chantal Cherifi

  • Department of Economics, Yildiz Technical University, Istanbul, Türkiye

    Murat Donduran

About the editors

Luis M. Rocha is the George J. Klir Professor of Systems Science at the Thomas J. Watson College of Engineering and Applied Science (Department of Systems Science and Industrial Engineering), Binghamton University (State University of New York), where he leads the Complex Adaptive Systems and Computational Intelligence (CASCI) lab. He is also Senior Fellow at the Instituto Gulbenkian da Ciencia, co-director of the Consortium for Social and Biomedical Complexity between Binghamton University and Indiana University, and a founding partner of the international Center for Excellence in Mental Health Sciences. He has been the director of the NSF-NRT Interdisciplinary Training Program in Complex Networks and Systems, and Professor of Informatics in the Luddy School of Informatics, Computing, and Engineering at Indiana University, where he was a member of the advisory council of the Indiana University Network Science Institute, and core faculty of the Cognitive Science Program. Dr. Rocha is a Fulbright Scholar and has been a Visiting Professor a the Center for Theoretical Physics at the Aix-Marseille University, France as well as the Neuroscience Program, at the Champalimaud Foundation and the NOVA School of Business and Economics in Portugal. His research is on complex networks & systems, computational & systems biology, and computational intelligence. He received his Ph.D in Systems Science in 1997 from the State University of New York at Binghamton. From 1998 to 2004, he was a permanent staff scientist at the Los Alamos National Laboratory, where he founded and led a Complex Systems Modeling Team from 1998 to 2002 and was part of the Santa Fe Institute research community. He has organized major conferences in the field, such as the Tenth International Conferenceon the Simulation and Synthesis of Living Systems (Alife X), the Ninth European Conference on Artificial Life (ECAL 2007), and Complex Networks 2019-2023. He has published many articles in scientific and technology journals and has been the recipient of several scholarships and awards. At Indiana University, he has received the Indiana University School of Informatics & Computing, Trustees Award for Teaching Excellence in 2006 and 2015 after developing the complex systems training program and syllabi for several courses. 

Hocine Cherifi received the Ph.D. from the National Polytechnic Institute, Grenoble, in 1984. He has been a professor of computer science at the University of Burgundy, Dijon, France, since 1999. Before moving to Dijon, he held faculty positions with Rouen University and Jean Monnet University, France. He has also held visiting positions with Yonsei University, South Korea; the University of Western Australia, Australia; the National Pintung University, Taiwan; and Galatasaray University, Turkey. He has published over 200 scientific papers in international refereed journals and conference proceedings. His current research interests include computer vision and complex networks. He held leading positions in more than 15 international conference organizations as the general chair and the program chair. He has served on more than 100 program committees. He is the Founder of the International Conference on Complex Networks and their Applications. He is a member of the editorial board of Computational Social Networks, PLOS One, IEEE Access, Journal of Imaging, Complex Systems, Quality and Quantity, and Scientific Reports. He is the Founding Editor-in-Chief of Applied Network Science and PLOS Complex Systems. 

Chantal CHERIFI received her PhD in Computer science from Corsica University, France, in 2011. Since 2014, she has worked as an Associate Professor at the DISP laboratory at the University of Lyon2, France. Her main research interests are information systems agility and big data management with applications on enterprise information systems and smart cities, using complex networks, ontologies, and Product Lifecycle Management (PLM) systems tools. She is involved in several International conference organizations: Complex Networks (Program Chair & Local Committee 2017, Poster Chair 2016), CompleNet 2016 (Poster Chair), PLM 2015 (Local Committee), and DICTAP 2011 (Local Committee). She serves as a member of International Conferences Program committees (Complex Networks [2017, 2016], CompletNet 2016, Complexis 2016, ISCRAM-med [2017, 2016, 2015], CSCESM 2014, SITIS [2015, 2014, 2013, 2012], ICIEIS [2013, 2011]) and Journal referee (IJCIM 2016, EPL 2015, Scientific Reports - Nature 2015) She is a member of EU Erasmus-Mundus programs (SmartLink (2012-2016), cLink program (2012-2016)). Her local responsibilities include being a Committee Lab member (Since 2016)and Lab seminar coorganizer (Since 2014). 

Murat Donduran is a Professor of Economics at the Department of Economics, YILDIZ Technical University Istanbul Türkiye, where he is the Director of the Graduate School of Social Sciences. He is also the Board member of in Turkish Economic Foundation. His research is on microeconomics, computational economics, firm dynamics and game theory. He received his Bachelor's and Master's Degrees in Economics from Marmara University, Istanbul, Türkiye, and a Ph.D. in Economics in 2000 from the YILDIZ Technical University. Since 2000 he has been a faculty member in the Faculty of Economic and Administrative Sciences at the YILDIZ Technical University. He has organized several conferences in the field such as YILDIZ International Conference on Social Sciences, the Annual International Conference on Social Sciences (2016-2020), and the International Conference on Economics (IceTea) 2019-2023. He has published many articles in scientific journals such as Games and Economic Behavior, Review of Industrial Organization, Physica A, and North American Journal of Economics and Finance.

Bibliographic Information

  • Book Title: Complex Networks & Their Applications XII

  • Book Subtitle: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023 Volume 1

  • Editors: Hocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-031-53468-3

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Hardcover ISBN: 978-3-031-53467-6Published: 20 February 2024

  • Softcover ISBN: 978-3-031-53470-6Due: 20 June 2024

  • eBook ISBN: 978-3-031-53468-3Published: 19 February 2024

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XXII, 466

  • Number of Illustrations: 53 b/w illustrations, 106 illustrations in colour

  • Topics: Complexity, Computational Intelligence

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