A novel classification method for paper-reviewer recommendation

Shu Zhao (), Dong Zhang (), Zhen Duan (), Jie Chen (), Yan-ping Zhang () and Jie Tang ()
Additional contact information
Shu Zhao: Anhui University
Dong Zhang: Anhui University
Zhen Duan: Anhui University
Jie Chen: Anhui University
Yan-ping Zhang: Anhui University
Jie Tang: Tsinghua University

Scientometrics, 2018, vol. 115, issue 3, No 10, 1293-1313

Abstract: Abstract Reviewer recommendation problem in the research field usually refers to invite experts to comment on the quality of papers, proposals, etc. How to effectively and accurately recommend reviewers for the submitted papers and proposals is a meaningful and still tough task. At present, many unsupervised recommendation methods have been researched to solve this task. In this paper, a novel classification method named Word Mover’s Distance–Constructive Covering Algorithm (WMD–CCA, for short) is proposed to solve the reviewer recommendation problem as a classification issue. A submission or a reviewer is described by some tags, such as keywords, research interests, and so on. First, the submission or the reviewer is represented as some vectors by a word embedding method. That is to say, each tag describing a submission or a reviewer is represented as a vector. Second, the Word Mover’s Distance (WMD, for short) method is used to measure the minimum distances between submissions and reviewers. Actually, the papers usually have research field information, and utilizing them well might improve the reviewer recommendation accuracy. So finally, the reviewer recommendation task is transformed into a classification problem which is solved by a supervised learning method- Constructive Covering Algorithm (CCA, for short). Comparative experiments are conducted with 4 public datasets and a synthetic dataset from Baidu Scholar, which show that the proposed method WMD–CCA effectively solves the reviewer recommendation task as a classification issue and improves the recommendation accuracy.

Keywords: Reviewer recommendation; Classification; Word embedding; Word Mover’s Distance; Constructive Covering Algorithm; 68T99 (search for similar items in EconPapers)
JEL-codes: C63 C89 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11192-018-2726-6

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