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World Conference on Information Systems and Technologies

WorldCIST 2020: Trends and Innovations in Information Systems and Technologies pp 523–530Cite as

A Comparative Study of Representation Learning Techniques for Dynamic Networks

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1161))

Abstract

Representation Learning in dynamic networks has gained increasingly more attention due to its promising applicability. In the literature, we can find two popular approaches that have been adapted to dynamic networks: random-walk based techniques and graph-autoencoders. Despite the popularity, no work has compared them in well-know datasets. We fill this gap by using two link prediction settings that evaluate the techniques. We find standard node2vec, a random-walk method, outperforms the graph-autoencoders.

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Author information

Authors and Affiliations

  1. Research Center for Information Systems Engineering (LIRIS), KU Leuven, Leuven, Belgium

    Carlos Ortega Vázquez, Sandra Mitrović, Jochen De Weerdt & Seppe vanden Broucke

  2. Department of Business Informatics and Operations Management, Ghent University, Ghent, Belgium

    Seppe vanden Broucke

Authors
  1. Carlos Ortega Vázquez
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  2. Sandra Mitrović
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  3. Jochen De Weerdt
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  4. Seppe vanden Broucke
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Corresponding author

Correspondence to Carlos Ortega Vázquez .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. FEUP, Universidade do Porto, Porto, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata, Italy

    Sandra Costanzo

  5. Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

    Irena Orovic

  6. Universidade Portucalense, Porto, Portugal

    Fernando Moreira

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© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

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Ortega Vázquez, C., Mitrović, S., De Weerdt, J., vanden Broucke, S. (2020). A Comparative Study of Representation Learning Techniques for Dynamic Networks. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1161. Springer, Cham. https://doi.org/10.1007/978-3-030-45697-9_51

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