The article is devoted to the task of expert assignment. The article provides an overview of methods, which are currently used to solve this task. We discuss the main problems of those methods and propose to leverage large collections of documents that are authored by the experts. The article describes a basic method for searching and ranking of experts for a given document, using similar document retrieval. For the evaluation of the proposed method we use private corpus of applications for a grant. Experimental studies show that the more documents are available that are authored by experts, the better recall becomes. In conclusion we discuss current limitations of proposed method and describe future work to use more features from texts, such as bibliography, co-authors information etc.
DOI: https://doi.org/10.14357/20718594190206
PDF at the Institute for Systems Analysis of Russian Academy of Sciences website (in Russian): www.isa.ru/aidt/images/documents/2019-02/62-71.pdf
At the Artificial Intelligence and Decision Making journal's website: http://aidt.ru/index.php?option=com_content&view=article&id=837&lang=en
D. V. Zubarev, I. V. Sochenkov, I. A. Tikhomirov, O. G. Gregoriev. Expert assignment method based on similar document retrieval from large text collections //Artificial Intelligence and Decision Making. – 2019. – №. 2. – Page 62-71.