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Author disambiguation is a problem of considerable relevance for information retrieval systems in the academic field. The AMiner name disambiguation algorithm represents one of the approaches based on Machine Learning with greater impact in the present. In this work, an evaluation of the AMiner name disambiguation algorithm is presented for author disambiguation in the context of a Computer Science academic metasearcher. The experimental results with data generated by the academic metasearcher warn about an average performance similar to the reference. Likewise, the experimental evaluations allow the identification of special cases of author names where the algorithm presents low performance when is compared to the average. This finding allowed to identify an apparent association between the low performance of the algorithm in contexts of several authors with the same name and with few publications.

Evaluación del algoritmo de desambiguación de autores de AMiner en un metabuscador académico de Ciencias de la Computación