Bibliometric study of the scientific research on “Learning to Rank” between 2000 and 2013

Oscar J. Alejo-Machado (), Juan Manuel Fernández-Luna () and Juan F. Huete ()
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Oscar J. Alejo-Machado: University of Cienfuegos
Juan Manuel Fernández-Luna: Universidad de Granada
Juan F. Huete: Universidad de Granada

Scientometrics, 2015, vol. 102, issue 2, No 31, 1669-1686

Abstract: Abstract The application of machine learning algorithms in the construction of ranking models is a relatively new research area which has emerged during the last 10 years within the field of artificial intelligence and information retrieval. This paper presents a bibliometric study of scientific output on learning to rank (L2R) between 2000 and 2013. For this procedure to be successful, every relevant bibliographic L2R record retrieved from the Scopus database was considered. The records were processed according to a series of one-dimensional and multi-dimensional metric indicators which were selected for the study. The results of this research provide the scientific community with reliable, up-to-date information about the state of L2R research and trends, and will enable researchers to develop valuable studies to reinforce research, development and innovation.

Keywords: Learning to rank; Bibliometric; Scientific production (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11192-014-1467-4

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