Yeonbin Son, Hyeontae An, Yerim Choi, Journal of Internet Computing and Services, Vol. 19, No. 4, pp. 27-33, Aug. 2018
10.7472/jksii.2018.19.4.27, Full Text:  HTML
Keywords: Manuscript proofreading, proofreader matching, topic modeling, importance of document

Abstract

In the process of submitting a manuscript to a journal in order to present the results of the research at the research institution, researchers often proofread the manuscript because it can manuscripts to communicate the results more effectively. Currently, most of the manuscript proofreading companies use the manual proofreader assignment method according to the subjective judgment of the matching manager. Therefore, in this paper, we propose a topic-based proofreader matching method for effective proofreading results. The proposed method is categorized into two steps. First, a topic modeling is performed by using Latent Dirichlet Allocation. In this process, the frequency of each document constituting the representative document of a user is determined according to the importance of the document. Second, the user similarity is calculated based on the cosine similarity method. In addition, we confirmed through experiments by using real-world dataset. The performance of the proposed method is superior to the comparative method, and the validity of the matching results was verified using qualitative evaluation.

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