Observatorio de I+D+i UPM

Memorias de investigación
Ponencias en congresos:
Predicting the h-index with cost-sensitive naive Bayes
Año:2011
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
Bibliometric indices are an increasingly important topic for the scientific community nowadays. One of the most successful bibliometric indices is the well-known h-index. In view of the attention attracted by this index, our research is based on the construction of several prediction models to forecast the h-index of Spanish professors (with a permanent position) for a four-year time horizon. We built two different types of models (junior models and senior models) to differentiate between professors' seniority. These models are learnt from bibliometric data using a cost-sensitive naive Bayes approach that takes into account the expected cost of instances predictions at classification time. Results show that it is easier to predict the h-index of the one-year time horizon than the others, that is, it has a higher average accuracy and lower average total cost than the others. Similarly, it is easier to predict the h-index of junior professors than senior professors.
Internacional
Si
Nombre congreso
11th International Conference on Intelligent Systems Design and Applications (ISDA 2011)
Tipo de participación
960
Lugar del congreso
Córdoba, Spain
Revisores
Si
ISBN o ISSN
978-1-4577-1676-8
DOI
Fecha inicio congreso
22/11/2011
Fecha fin congreso
24/11/2011
Desde la página
599
Hasta la página
604
Título de las actas
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications (ISDA 2011)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Alfonso Ibáñez Martín (UPM)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
  • Autor: Maria Concepcion Bielza Lozoya (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Inteligencia Artificial
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