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Problems and challenges of information resources producers’ clustering

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  • Cena, Anna
  • Gagolewski, Marek
  • Mesiar, Radko

Abstract

Classically, unsupervised machine learning techniques are applied on data sets with fixed number of attributes (variables). However, many problems encountered in the field of informetrics face us with the need to extend these kinds of methods in a way such that they may be computed over a set of nonincreasingly ordered vectors of unequal lengths. Thus, in this paper, some new dissimilarity measures (metrics) are introduced and studied. Owing to that we may use, e.g. hierarchical clustering algorithms in order to determine an input data set's partition consisting of sets of producers that are homogeneous not only with respect to the quality of information resources, but also their quantity.

Suggested Citation

  • Cena, Anna & Gagolewski, Marek & Mesiar, Radko, 2015. "Problems and challenges of information resources producers’ clustering," Journal of Informetrics, Elsevier, vol. 9(2), pages 273-284.
    • Handle: RePEc:eee:infome:v:9:y:2015:i:2:p:273-284
    DOI: 10.1016/j.joi.2015.02.005
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    References listed on IDEAS

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    1. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    2. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    3. Nieminen, Paavo & Pölönen, Ilkka & Sipola, Tuomo, 2013. "Research literature clustering using diffusion maps," Journal of Informetrics, Elsevier, vol. 7(4), pages 874-886.
    4. Schreiber, Michael, 2013. "A case study of the arbitrariness of the h-index and the highly-cited-publications indicator," Journal of Informetrics, Elsevier, vol. 7(2), pages 379-387.
    5. Ortega, José Luis & López-Romero, Elena & Fernández, Inés, 2011. "Multivariate approach to classify research institutes according to their outputs: The case of the CSIC's institutes," Journal of Informetrics, Elsevier, vol. 5(3), pages 323-332.
    6. Glenn Milligan, 1979. "Ultrametric hierarchical clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 44(3), pages 343-346, September.
    7. Woeginger, Gerhard J., 2008. "An axiomatic characterization of the Hirsch-index," Mathematical Social Sciences, Elsevier, vol. 56(2), pages 224-232, September.
    8. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    9. Gagolewski, Marek & Mesiar, Radko, 2012. "Aggregating different paper quality measures with a generalized h-index," Journal of Informetrics, Elsevier, vol. 6(4), pages 566-579.
    10. Gagolewski, Marek, 2013. "Scientific impact assessment cannot be fair," Journal of Informetrics, Elsevier, vol. 7(4), pages 792-802.
    11. Ying Cheng & Nian Cai Liu, 2006. "A first approach to the classification of the top 500 world universities by their disciplinary characteristics using scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 135-150, July.
    12. Gagolewski, Marek, 2011. "Bibliometric impact assessment with R and the CITAN package," Journal of Informetrics, Elsevier, vol. 5(4), pages 678-692.
    13. Waltman, Ludo & van Eck, Nees Jan & Noyons, Ed C.M., 2010. "A unified approach to mapping and clustering of bibliometric networks," Journal of Informetrics, Elsevier, vol. 4(4), pages 629-635.
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