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Ranking computer science conferences using self-organizing maps with dynamic node splitting

Author

Listed:
  • Vinicius da Silva Almendra

    (University of Bucharest)

  • Denis Enăchescu

    (University of Bucharest
    “Gheorghe Mihoc - Caius Iacob” Institute for Mathematical Statistics and Applied Mathematics)

  • Cornelia Enăchescu

    (“Gheorghe Mihoc - Caius Iacob” Institute for Mathematical Statistics and Applied Mathematics)

Abstract

Research dissemination in the Computer Science domain depends heavily on conference publications. The review processes of major conferences is rigorous and the work presented in those venues have more visibility and more citations than many journals, with the advantage of a faster dissemination of ideas. We consider that any evaluation system in the Computer Science domain must take into account conferences as having the same importance as journals. This makes the evaluation of venues an important issue. While journals are usually evaluated through their Impact Factor, there is no widely accepted method for evaluating conferences. In our work we analyzed the possibility of using Machine learning techniques to extend an existing ranking to new conferences, based on a set of measurements that are available for the majority of venues. Our proposal consists on the application of a Machine learning technique—self-organizing maps—with some extensions in order to classify new conferences based on an existing ranking. We also try to estimate the theoretical maximal accuracy that can be obtained using statistical learning techniques.

Suggested Citation

  • Vinicius da Silva Almendra & Denis Enăchescu & Cornelia Enăchescu, 2015. "Ranking computer science conferences using self-organizing maps with dynamic node splitting," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 267-283, January.
    • Handle: RePEc:spr:scient:v:102:y:2015:i:1:d:10.1007_s11192-014-1436-y
    DOI: 10.1007/s11192-014-1436-y
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    References listed on IDEAS

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    1. Waister Silva Martins & Marcos André Gonçalves & Alberto H. F. Laender & Nivio Ziviani, 2010. "Assessing the quality of scientific conferences based on bibliographic citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 133-155, April.
    2. Peep Küngas & Siim Karus & Svitlana Vakulenko & Marlon Dumas & Cristhian Parra & Fabio Casati, 2013. "Reverse-engineering conference rankings: what does it take to make a reputable conference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 651-665, August.
    3. Linda Butler, 2008. "ICT assessment: Moving beyond journal outputs," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(1), pages 39-55, January.
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