Algoritmos de clasificación de documentos científicos: pasado y presente
DOI:
https://doi.org/10.3145/infonomy.25.026Palabras clave:
Algoritmos de clasificación, Clasificaciones a nivel de documento, Clasificaciones, Clasificación de la ciencia, Bases de datos de ciencia, Cienciometría, Citación, Esquemas de clasificación, ASJC, Scopus, Web of ScienceResumen
Este trabajo se presenta como una recopilación de algoritmos de clasificación de la investigación a nivel de artículo como alternativa a las clasificaciones por revistas que se emplean en las grandes bases de datos de ciencia como Web of Science o Scopus, las cuales causan gran imprecisión en las búsquedas y en la evaluación de la ciencia, ya que utilizando éstas, los artículos no resultan categorizados con fidelidad respecto a su verdadero contenido. En primer lugar hacemos una revisión histórica de las principales ideas planteadas a lo largo de los años desde la misma aparición de las bases de datos, detectando sus contribuciones y sus limitaciones. Los algoritmos de agrupamiento automático y de detección de comunidades han supuesto grandes avances en organización de la ciencia, pero no resultan aplicables como alternativa a la clasificación por revistas. Otros algoritmos no son escalables al conjunto de la ciencia debido a su complejidad, como los basados en redes neuronales o minería de textos. Las propuestas más recientes y prometedoras responden a algoritmos sencillos que, partiendo de la categorización por revistas, reclasifican los artículos en las mismas jerarquías temáticas de las bases de datos, mediante el análisis de simples citas y referencias.Citas
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Derechos de autor 2025 Jesús M. Álvarez-Llorente, Vicente P. Guerrero-Bote, Félix De-Moya-Anegón
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