Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Collective Classification

  • Tomasz Kajdanowicz
  • Przemysław Kazienko
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_45





Is used to name a collection of network nodes that reasonably might be grouped together. Commonly encountered classes have simple unique textual descriptions – labels


Means assigning network nodes into predefined classes – giving them class labels (labeling). Having data about nodes that are already labeled (known nodes), we can derive some knowledge – train a classifier. A trained classifier is able to map (classify) the features of unknown nodes to classes – assign the class labels. For instance, we would like to allocate humans to those with and without disease based on their symptoms and illnesses of their parents. The common classification tasks accomplish either binary or multiclass classification. It means that a given data instance may be assigned with one of two or one of many classes, respectively

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This work was partially supported by the National Science Centre, Poland, the decisions no. 2016/21/D/ST6/02948 and DEC-2016/21/B/ST6/01463 by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 691152 (RENOIR); the Polish Ministry of Science and Higher Education fund for supporting internationally co-financed projects in 2016-2019 (agreement no. 3628/H2020/2016/2).


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Copyright information

© Springer Science+Business Media LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Computer Science and Management, Department of Computational IntelligenceWroclaw University of Science and TechnologyWrocławPoland
  2. 2.Department of Computational Intelligence, ENGINE – The European Centre for Data Science, Faculty of Computer Science and ManagementWroclaw University of Science and TechnologyWrocławPoland

Section editors and affiliations

  • Fakhreddine Karray
    • 1
  1. 1.Department of Electrical and Computer Engineering, Centre for Pattern Analysis and Machine Intelligence (CPAMI)University of WaterlooWaterlooCanada