Abstract
The paper describes the problems of automatic selection of experts for reviewing scientific texts. Existing methods are analyzed, and a new selection method is proposed, based on obtaining a ranked list of relevant experts by processing a large amount of unstructured data. A technique for evaluating the results of similar methods is proposed and the effectiveness of the proposed approaches are studied in experiments.
The research is supported by Russian Foundation for Basic Research (grant №18-29-03087).
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Shiray, M.A., Grigoriev, O.G. (2020). Method of Selecting Experts Based on Analysis of Large Unstructured Data and Their Relations. In: Kuznetsov, S.O., Panov, A.I., Yakovlev, K.S. (eds) Artificial Intelligence. RCAI 2020. Lecture Notes in Computer Science(), vol 12412. Springer, Cham. https://doi.org/10.1007/978-3-030-59535-7_22
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