Automatic Assignment of Reviewers to Papers Based on Vector Space Text Analysis Model
Yordan Kalmukov · 2020
The paper outlines a series of experiments aiming to test whether the vector space text analysis model could be successfully and reliably used to automatically determine the level of competence of a reviewer to evaluate a specific paper. The model corresponds to an implicit method of describing papers and reviewers' competences that does not require users to perform any additional actions. The similarity factors between papers and reviewers are calculated based on content analysis of publications' abstracts. The document collection consists of all submitted papers and reviewers' previous publications. The latter are retrieved from external Internet resources -- Semantic Scholar and DBLP.